Overview

Dataset statistics

 MasculinoFemenino
Number of variables2424
Number of observations7374120601
Missing cells10469930475
Missing cells (%)5.9%6.2%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory14.1 MiB3.9 MiB
Average record size in memory200.0 B200.0 B

Variable types

 MasculinoFemenino
Text1010
Unsupported66
DateTime11
Categorical55
Numeric22

Alerts

MasculinoFemenino
Sexo has constant value "Masculino" Sexo has constant value "Femenino" Constant
Edad_transcrito is highly overall correlated with Tipo_restosEdad_transcrito is highly overall correlated with Tipo_restosHigh Correlation
Tipo_restos is highly overall correlated with Edad_transcritoTipo_restos is highly overall correlated with Conocido_desconocido and 1 other fieldsHigh Correlation
Tipo_restos is highly imbalanced (88.6%) Tipo_restos is highly imbalanced (83.5%) Imbalance
Primer_apellido has 1468 (2.0%) missing values Primer_apellido has 377 (1.8%) missing values Missing
Nombres_propios has 1598 (2.2%) missing values Nombres_propios has 465 (2.3%) missing values Missing
Procedencia_alcaldia has 24167 (32.8%) missing values Procedencia_alcaldia has 7025 (34.1%) missing values Missing
Procedencia_acta has 19429 (26.3%) missing values Procedencia_acta has 5808 (28.2%) missing values Missing
Diagnostico_estandar has 6275 (8.5%) missing values Diagnostico_estandar has 1968 (9.6%) missing values Missing
Diagnostico_extendido has 6275 (8.5%) missing values Diagnostico_extendido has 1968 (9.6%) missing values Missing
Edad_transcrito has 44534 (60.4%) missing values Edad_transcrito has 12571 (61.0%) missing values Missing
ID has unique values ID has unique values Unique
Numero_progresivo_transcrito is an unsupported type, check if it needs cleaning or further analysis Numero_progresivo_transcrito is an unsupported type, check if it needs cleaning or further analysis Unsupported
Fecha_transcrito is an unsupported type, check if it needs cleaning or further analysis Fecha_transcrito is an unsupported type, check if it needs cleaning or further analysis Unsupported
Expediente_SEMEFO_transcrito is an unsupported type, check if it needs cleaning or further analysis Expediente_SEMEFO_transcrito is an unsupported type, check if it needs cleaning or further analysis Unsupported
Numero_acta_transcrito is an unsupported type, check if it needs cleaning or further analysis Numero_acta_transcrito is an unsupported type, check if it needs cleaning or further analysis Unsupported
Procedencia_acta is an unsupported type, check if it needs cleaning or further analysis Procedencia_acta is an unsupported type, check if it needs cleaning or further analysis Unsupported
Foja_transcrito is an unsupported type, check if it needs cleaning or further analysis Foja_transcrito is an unsupported type, check if it needs cleaning or further analysis Unsupported
Alert not present in this datasetConocido_desconocido is highly overall correlated with Tipo_restosHigh Correlation

Reproduction

 MasculinoFemenino
Analysis started2025-02-12 02:01:24.4668882025-02-12 02:01:31.386396
Analysis finished2025-02-12 02:01:31.3844642025-02-12 02:01:33.365650
Duration6.92 seconds1.98 second
Software versionydata-profiling v4.8.3ydata-profiling v4.8.3
Download configurationconfig.jsonconfig.json

Variables

ID
['Text', 'Text']

 MasculinoFemenino
Distinct7374120601
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:33.912721image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length1313
Median length1313
Mean length1313
Min length1313

Characters and Unicode

 MasculinoFemenino
Total characters958633267813
Distinct characters1313
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique7374120601 ?
Unique (%)100.0%100.0%

Sample

 MasculinoFemenino
1st rowBO_1968_00003BO_1968_00001
2nd rowBO_1968_00004BO_1968_00002
3rd rowBO_1968_00006BO_1968_00005
4th rowBO_1968_00007BO_1968_00012
5th rowBO_1968_00008BO_1968_00016
ValueCountFrequency (%)
bo_1968_00003 1
 
< 0.1%
bo_1969_01574 1
 
< 0.1%
bo_1968_00006 1
 
< 0.1%
bo_1968_00007 1
 
< 0.1%
bo_1968_00008 1
 
< 0.1%
bo_1968_00009 1
 
< 0.1%
bo_1968_00010 1
 
< 0.1%
bo_1968_00011 1
 
< 0.1%
bo_1968_00024 1
 
< 0.1%
bo_1968_00013 1
 
< 0.1%
Other values (73731) 73731
> 99.9%
ValueCountFrequency (%)
bo_1968_00001 1
 
< 0.1%
bo_1968_00732 1
 
< 0.1%
bo_1968_00012 1
 
< 0.1%
bo_1968_00016 1
 
< 0.1%
bo_1968_00018 1
 
< 0.1%
bo_1968_00026 1
 
< 0.1%
bo_1968_00029 1
 
< 0.1%
bo_1968_00040 1
 
< 0.1%
bo_1968_00072 1
 
< 0.1%
bo_1968_00042 1
 
< 0.1%
Other values (20591) 20591
> 99.9%
2025-02-11T20:01:34.258274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 147482
15.4%
0 117822
12.3%
1 117455
12.3%
9 104956
10.9%
7 77812
8.1%
B 73741
7.7%
O 73741
7.7%
8 48154
 
5.0%
2 43452
 
4.5%
6 41462
 
4.3%
Other values (3) 112556
11.7%
ValueCountFrequency (%)
_ 41202
15.4%
0 32819
12.3%
1 32589
12.2%
9 29094
10.9%
7 22259
8.3%
B 20601
7.7%
O 20601
7.7%
8 13241
 
4.9%
2 12323
 
4.6%
6 10965
 
4.1%
Other values (3) 32119
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 663669
69.2%
Connector Punctuation 147482
 
15.4%
Uppercase Letter 147482
 
15.4%
ValueCountFrequency (%)
Decimal Number 185409
69.2%
Connector Punctuation 41202
 
15.4%
Uppercase Letter 41202
 
15.4%

Most frequent character per category

Connector Punctuation
ValueCountFrequency (%)
_ 147482
100.0%
ValueCountFrequency (%)
_ 41202
100.0%
Decimal Number
ValueCountFrequency (%)
0 117822
17.8%
1 117455
17.7%
9 104956
15.8%
7 77812
11.7%
8 48154
7.3%
2 43452
 
6.5%
6 41462
 
6.2%
3 38511
 
5.8%
4 37849
 
5.7%
5 36196
 
5.5%
ValueCountFrequency (%)
0 32819
17.7%
1 32589
17.6%
9 29094
15.7%
7 22259
12.0%
8 13241
7.1%
2 12323
 
6.6%
6 10965
 
5.9%
4 10942
 
5.9%
3 10929
 
5.9%
5 10248
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 73741
50.0%
O 73741
50.0%
ValueCountFrequency (%)
B 20601
50.0%
O 20601
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 811151
84.6%
Latin 147482
 
15.4%
ValueCountFrequency (%)
Common 226611
84.6%
Latin 41202
 
15.4%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 147482
18.2%
0 117822
14.5%
1 117455
14.5%
9 104956
12.9%
7 77812
9.6%
8 48154
 
5.9%
2 43452
 
5.4%
6 41462
 
5.1%
3 38511
 
4.7%
4 37849
 
4.7%
ValueCountFrequency (%)
_ 41202
18.2%
0 32819
14.5%
1 32589
14.4%
9 29094
12.8%
7 22259
9.8%
8 13241
 
5.8%
2 12323
 
5.4%
6 10965
 
4.8%
4 10942
 
4.8%
3 10929
 
4.8%
Latin
ValueCountFrequency (%)
B 73741
50.0%
O 73741
50.0%
ValueCountFrequency (%)
B 20601
50.0%
O 20601
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 958633
100.0%
ValueCountFrequency (%)
ASCII 267813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 147482
15.4%
0 117822
12.3%
1 117455
12.3%
9 104956
10.9%
7 77812
8.1%
B 73741
7.7%
O 73741
7.7%
8 48154
 
5.0%
2 43452
 
4.5%
6 41462
 
4.3%
Other values (3) 112556
11.7%
ValueCountFrequency (%)
_ 41202
15.4%
0 32819
12.3%
1 32589
12.2%
9 29094
10.9%
7 22259
8.3%
B 20601
7.7%
O 20601
7.7%
8 13241
 
4.9%
2 12323
 
4.6%
6 10965
 
4.1%
Other values (3) 32119
12.0%
 MasculinoFemenino
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
 MasculinoFemenino
Distinct5714417817
Distinct (%)77.5%86.5%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:34.558442image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length132132
Median length4741
Mean length22.4217624.645503
Min length32

Characters and Unicode

 MasculinoFemenino
Total characters1653403507722
Distinct characters6055
Distinct categories98 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique5582217587 ?
Unique (%)75.7%85.4%

Sample

 MasculinoFemenino
1st rowarzate paredes juanacosta ortega teresa
2nd rowalvarez martinez isaacavila de cuestas catalina
3rd rowarce macedo justoarellano viuda de campos ma.
4th rowalvarez vela jesusalcantara viuda de borja ma.
5th rowavila ramirez pabloaguirre macias sara
ValueCountFrequency (%)
desconocido 12913
 
5.5%
de 4657
 
2.0%
hernandez 4437
 
1.9%
jose 4192
 
1.8%
garcia 3781
 
1.6%
martinez 3534
 
1.5%
con 3265
 
1.4%
gonzalez 2889
 
1.2%
lopez 2503
 
1.1%
juan 2460
 
1.1%
Other values (11113) 188655
80.9%
ValueCountFrequency (%)
de 4620
 
6.1%
maria 2489
 
3.3%
desconocida 1373
 
1.8%
hernandez 1366
 
1.8%
garcia 1132
 
1.5%
martinez 1052
 
1.4%
con 950
 
1.3%
ma 923
 
1.2%
gonzalez 854
 
1.1%
lopez 792
 
1.0%
Other values (5731) 60267
79.5%
2025-02-11T20:01:34.937835image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 174337
10.5%
o 166167
 
10.0%
e 160031
 
9.7%
159546
 
9.6%
r 127083
 
7.7%
n 109251
 
6.6%
i 98862
 
6.0%
c 81430
 
4.9%
l 76572
 
4.6%
d 74293
 
4.5%
Other values (50) 425831
25.8%
ValueCountFrequency (%)
a 71353
14.1%
55217
10.9%
e 50028
 
9.9%
r 39932
 
7.9%
o 33050
 
6.5%
i 32184
 
6.3%
n 30132
 
5.9%
l 24926
 
4.9%
d 22026
 
4.3%
c 21089
 
4.2%
Other values (45) 127785
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1467923
88.8%
Space Separator 159546
 
9.6%
Uppercase Letter 13058
 
0.8%
Other Punctuation 7823
 
0.5%
Decimal Number 4916
 
0.3%
Open Punctuation 59
 
< 0.1%
Close Punctuation 57
 
< 0.1%
Dash Punctuation 20
 
< 0.1%
Math Symbol 1
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 443667
87.4%
Space Separator 55217
 
10.9%
Uppercase Letter 3800
 
0.7%
Other Punctuation 3546
 
0.7%
Decimal Number 1433
 
0.3%
Close Punctuation 26
 
< 0.1%
Open Punctuation 26
 
< 0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 174337
11.9%
o 166167
11.3%
e 160031
10.9%
r 127083
 
8.7%
n 109251
 
7.4%
i 98862
 
6.7%
c 81430
 
5.5%
l 76572
 
5.2%
d 74293
 
5.1%
s 73157
 
5.0%
Other values (18) 326740
22.3%
ValueCountFrequency (%)
a 71353
16.1%
e 50028
11.3%
r 39932
 
9.0%
o 33050
 
7.4%
i 32184
 
7.3%
n 30132
 
6.8%
l 24926
 
5.6%
d 22026
 
5.0%
c 21089
 
4.8%
s 18224
 
4.1%
Other values (18) 100723
22.7%
Space Separator
ValueCountFrequency (%)
159546
100.0%
ValueCountFrequency (%)
55217
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6818
87.2%
" 751
 
9.6%
' 236
 
3.0%
, 6
 
0.1%
: 5
 
0.1%
# 4
 
0.1%
* 1
 
< 0.1%
/ 1
 
< 0.1%
? 1
 
< 0.1%
ValueCountFrequency (%)
. 3194
90.1%
" 246
 
6.9%
' 97
 
2.7%
: 3
 
0.1%
, 3
 
0.1%
/ 2
 
0.1%
? 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 3269
66.5%
6 1632
33.2%
2 8
 
0.2%
3 5
 
0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
1 950
66.3%
6 475
33.1%
3 5
 
0.3%
2 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
I 1632
12.5%
P 1632
12.5%
A 1632
12.5%
T 1632
12.5%
G 1632
12.5%
L 1632
12.5%
S 1632
12.5%
N 1632
12.5%
E 1
 
< 0.1%
B 1
 
< 0.1%
ValueCountFrequency (%)
I 475
12.5%
P 475
12.5%
T 475
12.5%
A 475
12.5%
G 475
12.5%
L 475
12.5%
S 475
12.5%
N 475
12.5%
Open Punctuation
ValueCountFrequency (%)
( 53
89.8%
[ 6
 
10.2%
ValueCountFrequency (%)
( 19
73.1%
[ 7
 
26.9%
Close Punctuation
ValueCountFrequency (%)
) 53
93.0%
] 4
 
7.0%
ValueCountFrequency (%)
) 19
73.1%
] 7
 
26.9%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1480981
89.6%
Common 172422
 
10.4%
ValueCountFrequency (%)
Latin 447467
88.1%
Common 60255
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 174337
11.8%
o 166167
11.2%
e 160031
10.8%
r 127083
 
8.6%
n 109251
 
7.4%
i 98862
 
6.7%
c 81430
 
5.5%
l 76572
 
5.2%
d 74293
 
5.0%
s 73157
 
4.9%
Other values (28) 339798
22.9%
ValueCountFrequency (%)
a 71353
15.9%
e 50028
11.2%
r 39932
 
8.9%
o 33050
 
7.4%
i 32184
 
7.2%
n 30132
 
6.7%
l 24926
 
5.6%
d 22026
 
4.9%
c 21089
 
4.7%
s 18224
 
4.1%
Other values (26) 104523
23.4%
Common
ValueCountFrequency (%)
159546
92.5%
. 6818
 
4.0%
1 3269
 
1.9%
6 1632
 
0.9%
" 751
 
0.4%
' 236
 
0.1%
( 53
 
< 0.1%
) 53
 
< 0.1%
- 20
 
< 0.1%
2 8
 
< 0.1%
Other values (12) 36
 
< 0.1%
ValueCountFrequency (%)
55217
91.6%
. 3194
 
5.3%
1 950
 
1.6%
6 475
 
0.8%
" 246
 
0.4%
' 97
 
0.2%
) 19
 
< 0.1%
( 19
 
< 0.1%
- 7
 
< 0.1%
[ 7
 
< 0.1%
Other values (9) 24
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1650138
99.8%
None 3265
 
0.2%
ValueCountFrequency (%)
ASCII 506770
99.8%
None 952
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 174337
10.6%
o 166167
 
10.1%
e 160031
 
9.7%
159546
 
9.7%
r 127083
 
7.7%
n 109251
 
6.6%
i 98862
 
6.0%
c 81430
 
4.9%
l 76572
 
4.6%
d 74293
 
4.5%
Other values (48) 422566
25.6%
ValueCountFrequency (%)
a 71353
14.1%
55217
10.9%
e 50028
 
9.9%
r 39932
 
7.9%
o 33050
 
6.5%
i 32184
 
6.4%
n 30132
 
5.9%
l 24926
 
4.9%
d 22026
 
4.3%
c 21089
 
4.2%
Other values (43) 126833
25.0%
None
ValueCountFrequency (%)
í 3264
> 99.9%
ñ 1
 
< 0.1%
ValueCountFrequency (%)
í 950
99.8%
ñ 2
 
0.2%

Primer_apellido
['Text', 'Text']

 MasculinoFemenino
Distinct60013352
Distinct (%)8.3%16.6%
Missing1468377
Missing (%)2.0%1.8%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:35.201268image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length2529
Median length2226
Mean length5.94274496.517504
Min length11

Characters and Unicode

 MasculinoFemenino
Total characters429500131810
Distinct characters3630
Distinct categories84 ?
Distinct scripts22 ?
Distinct blocks21 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique39642319 ?
Unique (%)5.5%11.5%

Sample

 MasculinoFemenino
1st rowarzateacosta
2nd rowalvarezavila
3rd rowarcearellano
4th rowalvarezalcantara
5th rowavilaaguirre
ValueCountFrequency (%)
s-d 13882
 
18.9%
hernandez 2209
 
3.0%
garcia 1942
 
2.6%
martinez 1790
 
2.4%
gonzalez 1445
 
2.0%
lopez 1270
 
1.7%
sanchez 1181
 
1.6%
rodriguez 1089
 
1.5%
perez 1086
 
1.5%
ramirez 1071
 
1.5%
Other values (5788) 46463
63.3%
ValueCountFrequency (%)
s-d 2278
 
10.5%
hernandez 726
 
3.3%
de 706
 
3.2%
garcia 618
 
2.8%
martinez 544
 
2.5%
gonzalez 469
 
2.2%
lopez 417
 
1.9%
sanchez 386
 
1.8%
rodriguez 379
 
1.7%
ramirez 327
 
1.5%
Other values (2885) 14918
68.5%
2025-02-11T20:01:35.527925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 57378
13.4%
e 45039
10.5%
r 41320
 
9.6%
s 31291
 
7.3%
o 30413
 
7.1%
d 26300
 
6.1%
n 26016
 
6.1%
z 24547
 
5.7%
i 21514
 
5.0%
l 21271
 
5.0%
Other values (26) 104411
24.3%
ValueCountFrequency (%)
a 18089
13.7%
e 14767
11.2%
r 13001
9.9%
o 9438
 
7.2%
n 8264
 
6.3%
z 7836
 
5.9%
s 7631
 
5.8%
i 6938
 
5.3%
d 6866
 
5.2%
l 6649
 
5.0%
Other values (20) 32331
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 414315
96.5%
Dash Punctuation 13884
 
3.2%
Space Separator 1159
 
0.3%
Other Punctuation 135
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Decimal Number 1
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 127784
96.9%
Dash Punctuation 2278
 
1.7%
Space Separator 1548
 
1.2%
Other Punctuation 200
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 57378
13.8%
e 45039
10.9%
r 41320
10.0%
s 31291
 
7.6%
o 30413
 
7.3%
d 26300
 
6.3%
n 26016
 
6.3%
z 24547
 
5.9%
i 21514
 
5.2%
l 21271
 
5.1%
Other values (17) 89226
21.5%
ValueCountFrequency (%)
a 18089
14.2%
e 14767
11.6%
r 13001
10.2%
o 9438
 
7.4%
n 8264
 
6.5%
z 7836
 
6.1%
s 7631
 
6.0%
i 6938
 
5.4%
d 6866
 
5.4%
l 6649
 
5.2%
Other values (16) 28305
22.2%
Dash Punctuation
ValueCountFrequency (%)
- 13884
100.0%
ValueCountFrequency (%)
- 2278
100.0%
Space Separator
ValueCountFrequency (%)
1159
100.0%
ValueCountFrequency (%)
1548
100.0%
Other Punctuation
ValueCountFrequency (%)
" 82
60.7%
. 50
37.0%
' 3
 
2.2%
ValueCountFrequency (%)
. 164
82.0%
" 36
 
18.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414315
96.5%
Common 15185
 
3.5%
ValueCountFrequency (%)
Latin 127784
96.9%
Common 4026
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 57378
13.8%
e 45039
10.9%
r 41320
10.0%
s 31291
 
7.6%
o 30413
 
7.3%
d 26300
 
6.3%
n 26016
 
6.3%
z 24547
 
5.9%
i 21514
 
5.2%
l 21271
 
5.1%
Other values (17) 89226
21.5%
ValueCountFrequency (%)
a 18089
14.2%
e 14767
11.6%
r 13001
10.2%
o 9438
 
7.4%
n 8264
 
6.5%
z 7836
 
6.1%
s 7631
 
6.0%
i 6938
 
5.4%
d 6866
 
5.4%
l 6649
 
5.2%
Other values (16) 28305
22.2%
Common
ValueCountFrequency (%)
- 13884
91.4%
1159
 
7.6%
" 82
 
0.5%
. 50
 
0.3%
[ 3
 
< 0.1%
' 3
 
< 0.1%
] 2
 
< 0.1%
+ 1
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
- 2278
56.6%
1548
38.5%
. 164
 
4.1%
" 36
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 429499
> 99.9%
None 1
 
< 0.1%
ValueCountFrequency (%)
ASCII 131810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 57378
13.4%
e 45039
10.5%
r 41320
 
9.6%
s 31291
 
7.3%
o 30413
 
7.1%
d 26300
 
6.1%
n 26016
 
6.1%
z 24547
 
5.7%
i 21514
 
5.0%
l 21271
 
5.0%
Other values (25) 104410
24.3%
ValueCountFrequency (%)
a 18089
13.7%
e 14767
11.2%
r 13001
9.9%
o 9438
 
7.2%
n 8264
 
6.3%
z 7836
 
5.9%
s 7631
 
5.8%
i 6938
 
5.3%
d 6866
 
5.2%
l 6649
 
5.0%
Other values (20) 32331
24.5%
None
ValueCountFrequency (%)
ñ 1
100.0%

Segundo_apellido
['Text', 'Text']

 MasculinoFemenino
Distinct61333689
Distinct (%)8.3%18.0%
Missing20857
Missing (%)0.3%0.3%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:35.890928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length2525
Median length2323
Mean length5.82418786.4762948
Min length11

Characters and Unicode

 MasculinoFemenino
Total characters428270133049
Distinct characters3834
Distinct categories76 ?
Distinct scripts22 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique40942419 ?
Unique (%)5.6%11.8%

Sample

 MasculinoFemenino
1st rowparedesortega
2nd rowmartinezde cuestas
3rd rowmacedoviuda de campos
4th rowvelaviuda de borja
5th rowramirezmacias
ValueCountFrequency (%)
s-d 16404
 
22.0%
hernandez 2226
 
3.0%
garcia 1836
 
2.5%
martinez 1740
 
2.3%
gonzalez 1442
 
1.9%
lopez 1225
 
1.6%
sanchez 1147
 
1.5%
rodriguez 1074
 
1.4%
perez 1028
 
1.4%
ramirez 997
 
1.3%
Other values (5777) 45580
61.0%
ValueCountFrequency (%)
s-d 3495
 
14.5%
de 2491
 
10.3%
hernandez 640
 
2.6%
garcia 514
 
2.1%
martinez 503
 
2.1%
viuda 392
 
1.6%
gonzalez 385
 
1.6%
lopez 374
 
1.5%
vda 354
 
1.5%
sanchez 344
 
1.4%
Other values (2678) 14660
60.7%
2025-02-11T20:01:36.217794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 55748
13.0%
e 44087
10.3%
r 39907
 
9.3%
s 33180
 
7.7%
o 29922
 
7.0%
d 28701
 
6.7%
n 25879
 
6.0%
z 23923
 
5.6%
i 21245
 
5.0%
l 20531
 
4.8%
Other values (28) 105147
24.6%
ValueCountFrequency (%)
a 16996
12.8%
e 15182
11.4%
r 11770
 
8.8%
d 10086
 
7.6%
o 8631
 
6.5%
s 8356
 
6.3%
n 7553
 
5.7%
z 6993
 
5.3%
i 6547
 
4.9%
l 6131
 
4.6%
Other values (24) 34804
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 410048
95.7%
Dash Punctuation 16405
 
3.8%
Space Separator 1166
 
0.3%
Other Punctuation 636
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Decimal Number 1
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 125041
94.0%
Space Separator 3608
 
2.7%
Dash Punctuation 3495
 
2.6%
Other Punctuation 903
 
0.7%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 55748
13.6%
e 44087
10.8%
r 39907
9.7%
s 33180
 
8.1%
o 29922
 
7.3%
d 28701
 
7.0%
n 25879
 
6.3%
z 23923
 
5.8%
i 21245
 
5.2%
l 20531
 
5.0%
Other values (16) 86925
21.2%
ValueCountFrequency (%)
a 16996
13.6%
e 15182
12.1%
r 11770
9.4%
d 10086
 
8.1%
o 8631
 
6.9%
s 8356
 
6.7%
n 7553
 
6.0%
z 6993
 
5.6%
i 6547
 
5.2%
l 6131
 
4.9%
Other values (17) 26796
21.4%
Dash Punctuation
ValueCountFrequency (%)
- 16405
100.0%
ValueCountFrequency (%)
- 3495
100.0%
Space Separator
ValueCountFrequency (%)
1166
100.0%
ValueCountFrequency (%)
3608
100.0%
Other Punctuation
ValueCountFrequency (%)
" 378
59.4%
' 134
 
21.1%
. 122
 
19.2%
, 1
 
0.2%
? 1
 
0.2%
ValueCountFrequency (%)
. 687
76.1%
" 156
 
17.3%
' 60
 
6.6%
Open Punctuation
ValueCountFrequency (%)
( 4
57.1%
[ 3
42.9%
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
57.1%
] 3
42.9%
ValueCountFrequency (%)
] 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 410048
95.7%
Common 18222
 
4.3%
ValueCountFrequency (%)
Latin 125041
94.0%
Common 8008
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 55748
13.6%
e 44087
10.8%
r 39907
9.7%
s 33180
 
8.1%
o 29922
 
7.3%
d 28701
 
7.0%
n 25879
 
6.3%
z 23923
 
5.8%
i 21245
 
5.2%
l 20531
 
5.0%
Other values (16) 86925
21.2%
ValueCountFrequency (%)
a 16996
13.6%
e 15182
12.1%
r 11770
9.4%
d 10086
 
8.1%
o 8631
 
6.9%
s 8356
 
6.7%
n 7553
 
6.0%
z 6993
 
5.6%
i 6547
 
5.2%
l 6131
 
4.9%
Other values (17) 26796
21.4%
Common
ValueCountFrequency (%)
- 16405
90.0%
1166
 
6.4%
" 378
 
2.1%
' 134
 
0.7%
. 122
 
0.7%
( 4
 
< 0.1%
) 4
 
< 0.1%
] 3
 
< 0.1%
[ 3
 
< 0.1%
, 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
3608
45.1%
- 3495
43.6%
. 687
 
8.6%
" 156
 
1.9%
' 60
 
0.7%
[ 1
 
< 0.1%
] 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 428270
100.0%
ValueCountFrequency (%)
ASCII 133047
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 55748
13.0%
e 44087
10.3%
r 39907
 
9.3%
s 33180
 
7.7%
o 29922
 
7.0%
d 28701
 
6.7%
n 25879
 
6.0%
z 23923
 
5.6%
i 21245
 
5.0%
l 20531
 
4.8%
Other values (28) 105147
24.6%
ValueCountFrequency (%)
a 16996
12.8%
e 15182
11.4%
r 11770
 
8.8%
d 10086
 
7.6%
o 8631
 
6.5%
s 8356
 
6.3%
n 7553
 
5.7%
z 6993
 
5.3%
i 6547
 
4.9%
l 6131
 
4.6%
Other values (23) 34802
26.2%
None
ValueCountFrequency (%)
ñ 2
100.0%

Nombres_propios
['Text', 'Text']

 MasculinoFemenino
Distinct52362927
Distinct (%)7.3%14.5%
Missing1598465
Missing (%)2.2%2.3%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:36.477696image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length5525
Median length3022
Mean length6.17890867.2853596
Min length11

Characters and Unicode

 MasculinoFemenino
Total characters445765146698
Distinct characters4433
Distinct categories86 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique37182016 ?
Unique (%)5.2%10.0%

Sample

 MasculinoFemenino
1st rowjuanteresa
2nd rowisaaccatalina
3rd rowjustoma.
4th rowjesusma.
5th rowpablosara
ValueCountFrequency (%)
s-d 13785
 
17.2%
jose 4126
 
5.2%
juan 2398
 
3.0%
luis 2152
 
2.7%
antonio 1747
 
2.2%
francisco 1654
 
2.1%
jesus 1640
 
2.0%
manuel 1511
 
1.9%
j 1342
 
1.7%
pedro 1122
 
1.4%
Other values (2634) 48576
60.7%
ValueCountFrequency (%)
maria 2515
 
10.0%
s-d 2208
 
8.7%
ma 845
 
3.3%
guadalupe 668
 
2.6%
carmen 529
 
2.1%
de 487
 
1.9%
juana 418
 
1.7%
rosa 391
 
1.5%
del 363
 
1.4%
margarita 305
 
1.2%
Other values (1637) 16517
65.4%
2025-02-11T20:01:36.801985image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 49368
11.1%
a 42783
 
9.6%
e 39068
 
8.8%
s 36374
 
8.2%
r 34006
 
7.6%
i 32825
 
7.4%
n 29160
 
6.5%
d 27255
 
6.1%
l 24868
 
5.6%
u 18366
 
4.1%
Other values (34) 111692
25.1%
ValueCountFrequency (%)
a 29264
19.9%
i 13972
9.5%
e 12620
 
8.6%
r 11641
 
7.9%
l 9263
 
6.3%
n 8099
 
5.5%
s 7610
 
5.2%
d 6732
 
4.6%
m 6716
 
4.6%
o 6184
 
4.2%
Other values (23) 34597
23.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 420849
94.4%
Dash Punctuation 13789
 
3.1%
Space Separator 7915
 
1.8%
Other Punctuation 3191
 
0.7%
Open Punctuation 8
 
< 0.1%
Close Punctuation 8
 
< 0.1%
Decimal Number 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 138101
94.1%
Space Separator 5110
 
3.5%
Dash Punctuation 2208
 
1.5%
Other Punctuation 1271
 
0.9%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
33.3%
3 1
33.3%
2 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
o 49368
11.7%
a 42783
10.2%
e 39068
9.3%
s 36374
8.6%
r 34006
 
8.1%
i 32825
 
7.8%
n 29160
 
6.9%
d 27255
 
6.5%
l 24868
 
5.9%
u 18366
 
4.4%
Other values (16) 86776
20.6%
ValueCountFrequency (%)
a 29264
21.2%
i 13972
10.1%
e 12620
9.1%
r 11641
 
8.4%
l 9263
 
6.7%
n 8099
 
5.9%
s 7610
 
5.5%
d 6732
 
4.9%
m 6716
 
4.9%
o 6184
 
4.5%
Other values (16) 26000
18.8%
Dash Punctuation
ValueCountFrequency (%)
- 13789
100.0%
ValueCountFrequency (%)
- 2208
100.0%
Space Separator
ValueCountFrequency (%)
7915
100.0%
ValueCountFrequency (%)
5110
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3047
95.5%
" 128
 
4.0%
' 9
 
0.3%
, 4
 
0.1%
/ 1
 
< 0.1%
: 1
 
< 0.1%
* 1
 
< 0.1%
ValueCountFrequency (%)
. 1247
98.1%
" 22
 
1.7%
, 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 7
87.5%
[ 1
 
12.5%
ValueCountFrequency (%)
[ 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
87.5%
] 1
 
12.5%
ValueCountFrequency (%)
] 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
E 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 420851
94.4%
Common 24914
 
5.6%
ValueCountFrequency (%)
Latin 138101
94.1%
Common 8597
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 49368
11.7%
a 42783
10.2%
e 39068
9.3%
s 36374
8.6%
r 34006
 
8.1%
i 32825
 
7.8%
n 29160
 
6.9%
d 27255
 
6.5%
l 24868
 
5.9%
u 18366
 
4.4%
Other values (18) 86778
20.6%
ValueCountFrequency (%)
a 29264
21.2%
i 13972
10.1%
e 12620
9.1%
r 11641
 
8.4%
l 9263
 
6.7%
n 8099
 
5.9%
s 7610
 
5.5%
d 6732
 
4.9%
m 6716
 
4.9%
o 6184
 
4.5%
Other values (16) 26000
18.8%
Common
ValueCountFrequency (%)
- 13789
55.3%
7915
31.8%
. 3047
 
12.2%
" 128
 
0.5%
' 9
 
< 0.1%
( 7
 
< 0.1%
) 7
 
< 0.1%
, 4
 
< 0.1%
[ 1
 
< 0.1%
/ 1
 
< 0.1%
Other values (6) 6
 
< 0.1%
ValueCountFrequency (%)
5110
59.4%
- 2208
25.7%
. 1247
 
14.5%
" 22
 
0.3%
[ 4
 
< 0.1%
] 4
 
< 0.1%
, 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445765
100.0%
ValueCountFrequency (%)
ASCII 146698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 49368
11.1%
a 42783
 
9.6%
e 39068
 
8.8%
s 36374
 
8.2%
r 34006
 
7.6%
i 32825
 
7.4%
n 29160
 
6.5%
d 27255
 
6.1%
l 24868
 
5.6%
u 18366
 
4.1%
Other values (34) 111692
25.1%
ValueCountFrequency (%)
a 29264
19.9%
i 13972
9.5%
e 12620
 
8.6%
r 11641
 
7.9%
l 9263
 
6.3%
n 8099
 
5.5%
s 7610
 
5.2%
d 6732
 
4.6%
m 6716
 
4.6%
o 6184
 
4.2%
Other values (23) 34597
23.6%

Fecha_transcrito
Unsupported

 MasculinoFemenino
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
 MasculinoFemenino
Distinct54795260
Distinct (%)7.4%25.6%
Missing13855
Missing (%)0.2%0.3%
Memory size1.1 MiB321.9 KiB
 MasculinoFemenino
Minimum1968-01-01 00:00:001968-01-02 00:00:00
Maximum1982-12-31 00:00:001982-12-31 00:00:00
2025-02-11T20:01:36.956635image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2025-02-11T20:01:37.102698image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
 MasculinoFemenino
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB

Procedencia_estandar
['Text', 'Text']

 MasculinoFemenino
Distinct108100
Distinct (%)0.1%0.5%
Missing29487
Missing (%)0.4%0.4%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:37.347847image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length85
Median length33
Mean length2.99897893.0194989
Min length22

Characters and Unicode

 MasculinoFemenino
Total characters22026661942
Distinct characters3830
Distinct categories53 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique615 ?
Unique (%)< 0.1%0.1%

Sample

 MasculinoFemenino
1st rowS-DS-D
2nd rowS-DS-D
3rd rowS-DS-D
4th rowS-DS-D
5th rowS-DS-D
ValueCountFrequency (%)
s-d 20281
27.6%
32a 2789
 
3.8%
33a 2435
 
3.3%
37a 2218
 
3.0%
1a 1943
 
2.6%
htb 1811
 
2.5%
20a 1748
 
2.4%
35a 1649
 
2.2%
13a 1547
 
2.1%
36a 1480
 
2.0%
Other values (99) 35548
48.4%
ValueCountFrequency (%)
s-d 5943
29.0%
32a 820
 
4.0%
33a 589
 
2.9%
37a 577
 
2.8%
htb 451
 
2.2%
20a 450
 
2.2%
36a 447
 
2.2%
hcm 437
 
2.1%
24a 426
 
2.1%
34a 419
 
2.0%
Other values (90) 9955
48.5%
2025-02-11T20:01:37.611246image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 40189
18.2%
- 28580
13.0%
S 20301
9.2%
D 20283
9.2%
3 18551
8.4%
1 16195
 
7.4%
2 15159
 
6.9%
H 8656
 
3.9%
C 5905
 
2.7%
4 4750
 
2.2%
Other values (28) 41697
18.9%
ValueCountFrequency (%)
A 10901
17.6%
- 8432
13.6%
S 5950
9.6%
D 5943
9.6%
3 4926
8.0%
1 4455
 
7.2%
2 4117
 
6.6%
H 2538
 
4.1%
C 1752
 
2.8%
4 1330
 
2.1%
Other values (20) 11598
18.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 118241
53.7%
Decimal Number 73425
33.3%
Dash Punctuation 28580
 
13.0%
Lowercase Letter 18
 
< 0.1%
Space Separator 2
 
< 0.1%
ValueCountFrequency (%)
Uppercase Letter 33357
53.9%
Decimal Number 20153
32.5%
Dash Punctuation 8432
 
13.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6
33.3%
z 2
 
11.1%
t 2
 
11.1%
c 2
 
11.1%
l 2
 
11.1%
p 2
 
11.1%
o 2
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 40189
34.0%
S 20301
17.2%
D 20283
17.2%
H 8656
 
7.3%
C 5905
 
5.0%
M 3771
 
3.2%
T 3429
 
2.9%
B 2355
 
2.0%
V 2312
 
2.0%
R 2227
 
1.9%
Other values (9) 8813
 
7.5%
ValueCountFrequency (%)
A 10901
32.7%
S 5950
17.8%
D 5943
17.8%
H 2538
 
7.6%
C 1752
 
5.3%
M 1209
 
3.6%
T 852
 
2.6%
B 664
 
2.0%
R 635
 
1.9%
V 604
 
1.8%
Other values (9) 2309
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 28580
100.0%
ValueCountFrequency (%)
- 8432
100.0%
Decimal Number
ValueCountFrequency (%)
3 18551
25.3%
1 16195
22.1%
2 15159
20.6%
4 4750
 
6.5%
7 4361
 
5.9%
5 3917
 
5.3%
6 3413
 
4.6%
8 2432
 
3.3%
0 2397
 
3.3%
9 2250
 
3.1%
ValueCountFrequency (%)
3 4926
24.4%
1 4455
22.1%
2 4117
20.4%
4 1330
 
6.6%
5 1136
 
5.6%
7 1124
 
5.6%
6 959
 
4.8%
8 764
 
3.8%
0 696
 
3.5%
9 646
 
3.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 118259
53.7%
Common 102007
46.3%
ValueCountFrequency (%)
Latin 33357
53.9%
Common 28585
46.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 40189
34.0%
S 20301
17.2%
D 20283
17.2%
H 8656
 
7.3%
C 5905
 
5.0%
M 3771
 
3.2%
T 3429
 
2.9%
B 2355
 
2.0%
V 2312
 
2.0%
R 2227
 
1.9%
Other values (16) 8831
 
7.5%
ValueCountFrequency (%)
A 10901
32.7%
S 5950
17.8%
D 5943
17.8%
H 2538
 
7.6%
C 1752
 
5.3%
M 1209
 
3.6%
T 852
 
2.6%
B 664
 
2.0%
R 635
 
1.9%
V 604
 
1.8%
Other values (9) 2309
 
6.9%
Common
ValueCountFrequency (%)
- 28580
28.0%
3 18551
18.2%
1 16195
15.9%
2 15159
14.9%
4 4750
 
4.7%
7 4361
 
4.3%
5 3917
 
3.8%
6 3413
 
3.3%
8 2432
 
2.4%
0 2397
 
2.3%
Other values (2) 2252
 
2.2%
ValueCountFrequency (%)
- 8432
29.5%
3 4926
17.2%
1 4455
15.6%
2 4117
14.4%
4 1330
 
4.7%
5 1136
 
4.0%
7 1124
 
3.9%
6 959
 
3.4%
8 764
 
2.7%
0 696
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220266
100.0%
ValueCountFrequency (%)
ASCII 61942
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 40189
18.2%
- 28580
13.0%
S 20301
9.2%
D 20283
9.2%
3 18551
8.4%
1 16195
 
7.4%
2 15159
 
6.9%
H 8656
 
3.9%
C 5905
 
2.7%
4 4750
 
2.2%
Other values (28) 41697
18.9%
ValueCountFrequency (%)
A 10901
17.6%
- 8432
13.6%
S 5950
9.6%
D 5943
9.6%
3 4926
8.0%
1 4455
 
7.2%
2 4117
 
6.6%
H 2538
 
4.1%
C 1752
 
2.8%
4 1330
 
2.1%
Other values (20) 11598
18.7%

Procedencia_direccion
['Text', 'Text']

 MasculinoFemenino
Distinct9793
Distinct (%)0.1%0.5%
Missing31394
Missing (%)0.4%0.5%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:37.888526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length9595
Median length7472
Mean length32.35410232.388843
Min length22

Characters and Unicode

 MasculinoFemenino
Total characters2375697664198
Distinct characters6464
Distinct categories88 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique39 ?
Unique (%)< 0.1%< 0.1%

Sample

 MasculinoFemenino
1st rowSin datosSin datos
2nd rowSin datosSin datos
3rd rowSin datosSin datos
4th rowSin datosSin datos
5th rowSin datosSin datos
ValueCountFrequency (%)
col 46424
 
12.9%
ministerio 37316
 
10.4%
público 37316
 
10.4%
sin 20283
 
5.6%
datos 20283
 
5.6%
balbuena 7895
 
2.2%
coordinación 7360
 
2.0%
territorial 7360
 
2.0%
1 6280
 
1.7%
hospital 6051
 
1.7%
Other values (149) 163238
45.4%
ValueCountFrequency (%)
col 12882
 
12.8%
ministerio 10128
 
10.1%
público 10128
 
10.1%
sin 5942
 
5.9%
datos 5942
 
5.9%
territorial 2212
 
2.2%
coordinación 2212
 
2.2%
balbuena 1918
 
1.9%
1 1710
 
1.7%
hospital 1693
 
1.7%
Other values (147) 45900
45.6%
2025-02-11T20:01:38.239820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
286378
 
12.1%
i 228232
 
9.6%
o 227011
 
9.6%
a 156147
 
6.6%
l 139580
 
5.9%
n 131993
 
5.6%
r 130430
 
5.5%
e 109598
 
4.6%
t 94770
 
4.0%
s 82543
 
3.5%
Other values (54) 789015
33.2%
ValueCountFrequency (%)
80160
 
12.1%
o 63760
 
9.6%
i 63658
 
9.6%
a 43513
 
6.6%
l 38274
 
5.8%
r 36908
 
5.6%
n 36673
 
5.5%
e 30408
 
4.6%
t 26872
 
4.0%
s 23117
 
3.5%
Other values (54) 220855
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1625374
68.4%
Space Separator 286378
 
12.1%
Uppercase Letter 285841
 
12.0%
Decimal Number 76599
 
3.2%
Close Punctuation 49382
 
2.1%
Open Punctuation 49382
 
2.1%
Other Punctuation 2124
 
0.1%
Other Letter 617
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 454952
68.5%
Space Separator 80160
 
12.1%
Uppercase Letter 79815
 
12.0%
Decimal Number 21192
 
3.2%
Open Punctuation 13646
 
2.1%
Close Punctuation 13646
 
2.1%
Other Punctuation 620
 
0.1%
Other Letter 167
 
< 0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
286378
100.0%
ValueCountFrequency (%)
80160
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 228232
14.0%
o 227011
14.0%
a 156147
9.6%
l 139580
8.6%
n 131993
8.1%
r 130430
8.0%
e 109598
6.7%
t 94770
 
5.8%
s 82543
 
5.1%
c 67541
 
4.2%
Other values (17) 257529
15.8%
ValueCountFrequency (%)
o 63760
14.0%
i 63658
14.0%
a 43513
9.6%
l 38274
8.4%
r 36908
8.1%
n 36673
8.1%
e 30408
6.7%
t 26872
 
5.9%
s 23117
 
5.1%
c 18794
 
4.1%
Other values (17) 72975
16.0%
Uppercase Letter
ValueCountFrequency (%)
C 67773
23.7%
M 49336
17.3%
P 43324
15.2%
S 30874
10.8%
T 17181
 
6.0%
B 12947
 
4.5%
A 9467
 
3.3%
G 9218
 
3.2%
H 9186
 
3.2%
V 8028
 
2.8%
Other values (12) 28507
10.0%
ValueCountFrequency (%)
C 19080
23.9%
M 13490
16.9%
P 11797
14.8%
S 9183
11.5%
T 5156
 
6.5%
B 3361
 
4.2%
H 2576
 
3.2%
A 2564
 
3.2%
G 2548
 
3.2%
V 2197
 
2.8%
Other values (12) 7863
9.9%
Close Punctuation
ValueCountFrequency (%)
) 49382
100.0%
ValueCountFrequency (%)
) 13646
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49382
100.0%
ValueCountFrequency (%)
( 13646
100.0%
Decimal Number
ValueCountFrequency (%)
3 18550
24.2%
2 17058
22.3%
1 16192
21.1%
4 4750
 
6.2%
7 4361
 
5.7%
5 3915
 
5.1%
0 3678
 
4.8%
6 3413
 
4.5%
8 2432
 
3.2%
9 2250
 
2.9%
ValueCountFrequency (%)
3 4925
23.2%
2 4721
22.3%
1 4455
21.0%
4 1330
 
6.3%
5 1135
 
5.4%
0 1133
 
5.3%
7 1124
 
5.3%
6 959
 
4.5%
8 764
 
3.6%
9 646
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2124
100.0%
ValueCountFrequency (%)
. 620
100.0%
Other Letter
ValueCountFrequency (%)
ª 617
100.0%
ValueCountFrequency (%)
ª 167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1911832
80.5%
Common 463865
 
19.5%
ValueCountFrequency (%)
Latin 534934
80.5%
Common 129264
 
19.5%

Most frequent character per script

Common
ValueCountFrequency (%)
286378
61.7%
) 49382
 
10.6%
( 49382
 
10.6%
3 18550
 
4.0%
2 17058
 
3.7%
1 16192
 
3.5%
4 4750
 
1.0%
7 4361
 
0.9%
5 3915
 
0.8%
0 3678
 
0.8%
Other values (4) 10219
 
2.2%
ValueCountFrequency (%)
80160
62.0%
( 13646
 
10.6%
) 13646
 
10.6%
3 4925
 
3.8%
2 4721
 
3.7%
1 4455
 
3.4%
4 1330
 
1.0%
5 1135
 
0.9%
0 1133
 
0.9%
7 1124
 
0.9%
Other values (4) 2989
 
2.3%
Latin
ValueCountFrequency (%)
i 228232
11.9%
o 227011
11.9%
a 156147
 
8.2%
l 139580
 
7.3%
n 131993
 
6.9%
r 130430
 
6.8%
e 109598
 
5.7%
t 94770
 
5.0%
s 82543
 
4.3%
C 67773
 
3.5%
Other values (40) 543755
28.4%
ValueCountFrequency (%)
o 63760
11.9%
i 63658
11.9%
a 43513
 
8.1%
l 38274
 
7.2%
r 36908
 
6.9%
n 36673
 
6.9%
e 30408
 
5.7%
t 26872
 
5.0%
s 23117
 
4.3%
C 19080
 
3.6%
Other values (40) 152671
28.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2308046
97.2%
None 67651
 
2.8%
ValueCountFrequency (%)
ASCII 645160
97.1%
None 19038
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
286378
 
12.4%
i 228232
 
9.9%
o 227011
 
9.8%
a 156147
 
6.8%
l 139580
 
6.0%
n 131993
 
5.7%
r 130430
 
5.7%
e 109598
 
4.7%
t 94770
 
4.1%
s 82543
 
3.6%
Other values (46) 721364
31.3%
ValueCountFrequency (%)
80160
 
12.4%
o 63760
 
9.9%
i 63658
 
9.9%
a 43513
 
6.7%
l 38274
 
5.9%
r 36908
 
5.7%
n 36673
 
5.7%
e 30408
 
4.7%
t 26872
 
4.2%
s 23117
 
3.6%
Other values (46) 201817
31.3%
None
ValueCountFrequency (%)
ú 37320
55.2%
ó 12813
 
18.9%
á 6312
 
9.3%
í 5187
 
7.7%
é 3980
 
5.9%
ñ 960
 
1.4%
ª 617
 
0.9%
Á 462
 
0.7%
ValueCountFrequency (%)
ú 10130
53.2%
ó 3683
 
19.3%
á 1922
 
10.1%
é 1359
 
7.1%
í 1318
 
6.9%
ñ 331
 
1.7%
ª 167
 
0.9%
Á 128
 
0.7%
 MasculinoFemenino
Distinct1616
Distinct (%)< 0.1%0.1%
Missing241677025
Missing (%)32.8%34.1%
Memory size1.1 MiB321.9 KiB
Cuauhtémoc
8162 
Miguel Hidalgo
7959 
Gustavo A. Madero
6854 
Benito Juárez
6455 
Venustiano Carranza
5992 
Other values (11)
14152 
Miguel Hidalgo
2336 
Cuauhtémoc
2181 
Benito Juárez
1988 
Gustavo A. Madero
1852 
Venustiano Carranza
1506 
Other values (11)
3713 

Length

 MasculinoFemenino
Max length1919
Median length1717
Mean length13.10225113.118739
Min length77

Characters and Unicode

 MasculinoFemenino
Total characters649531178100
Distinct characters3939
Distinct categories44 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique00 ?
Unique (%)0.0%0.0%

Sample

 MasculinoFemenino
1st rowCuauhtémocBenito Juárez
2nd rowCuauhtémocIztapalapa
3rd rowCoyoacánCuauhtémoc
4th rowCuauhtémocCuauhtémoc
5th rowCuauhtémocGustavo A. Madero

Common Values

ValueCountFrequency (%)
Cuauhtémoc 8162
 
11.1%
Miguel Hidalgo 7959
 
10.8%
Gustavo A. Madero 6854
 
9.3%
Benito Juárez 6455
 
8.8%
Venustiano Carranza 5992
 
8.1%
Iztacalco 3221
 
4.4%
Coyoacán 1973
 
2.7%
Álvaro Obregón 1828
 
2.5%
Iztapalapa 1792
 
2.4%
Azcapotzalco 1668
 
2.3%
Other values (6) 3670
 
5.0%
(Missing) 24167
32.8%
ValueCountFrequency (%)
Miguel Hidalgo 2336
 
11.3%
Cuauhtémoc 2181
 
10.6%
Benito Juárez 1988
 
9.7%
Gustavo A. Madero 1852
 
9.0%
Venustiano Carranza 1506
 
7.3%
Iztacalco 854
 
4.1%
Coyoacán 556
 
2.7%
Álvaro Obregón 554
 
2.7%
Iztapalapa 456
 
2.2%
Azcapotzalco 422
 
2.0%
Other values (6) 871
 
4.2%
(Missing) 7025
34.1%

Length

2025-02-11T20:01:38.314535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Masculino


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

Femenino


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
cuauhtémoc 8162
9.5%
hidalgo 7959
9.3%
miguel 7959
9.3%
gustavo 6854
8.0%
a 6854
8.0%
madero 6854
8.0%
benito 6455
 
7.5%
juárez 6455
 
7.5%
venustiano 5992
 
7.0%
carranza 5992
 
7.0%
Other values (14) 16442
19.1%
ValueCountFrequency (%)
miguel 2336
9.8%
hidalgo 2336
9.8%
cuauhtémoc 2181
9.2%
benito 1988
8.4%
juárez 1988
8.4%
gustavo 1852
7.8%
a 1852
7.8%
madero 1852
7.8%
venustiano 1506
 
6.3%
carranza 1506
 
6.3%
Other values (14) 4401
18.5%

Most occurring characters

ValueCountFrequency (%)
a 80771
 
12.4%
o 56755
 
8.7%
u 44587
 
6.9%
36404
 
5.6%
e 36091
 
5.6%
t 34606
 
5.3%
i 31035
 
4.8%
n 30048
 
4.6%
l 29553
 
4.5%
r 29223
 
4.5%
Other values (29) 240458
37.0%
ValueCountFrequency (%)
a 21340
 
12.0%
o 15518
 
8.7%
u 12281
 
6.9%
e 10382
 
5.8%
10222
 
5.7%
t 9393
 
5.3%
i 8734
 
4.9%
l 8204
 
4.6%
n 8094
 
4.5%
r 8039
 
4.5%
Other values (29) 65893
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 520295
80.1%
Uppercase Letter 85978
 
13.2%
Space Separator 36404
 
5.6%
Other Punctuation 6854
 
1.1%
ValueCountFrequency (%)
Lowercase Letter 142228
79.9%
Uppercase Letter 23798
 
13.4%
Space Separator 10222
 
5.7%
Other Punctuation 1852
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 80771
15.5%
o 56755
10.9%
u 44587
 
8.6%
e 36091
 
6.9%
t 34606
 
6.7%
i 31035
 
6.0%
n 30048
 
5.8%
l 29553
 
5.7%
r 29223
 
5.6%
c 22182
 
4.3%
Other values (14) 125444
24.1%
ValueCountFrequency (%)
a 21340
15.0%
o 15518
10.9%
u 12281
 
8.6%
e 10382
 
7.3%
t 9393
 
6.6%
i 8734
 
6.1%
l 8204
 
5.8%
n 8094
 
5.7%
r 8039
 
5.7%
c 5733
 
4.0%
Other values (14) 34510
24.3%
Space Separator
ValueCountFrequency (%)
36404
100.0%
ValueCountFrequency (%)
10222
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 17009
19.8%
M 15275
17.8%
A 8710
10.1%
H 7959
9.3%
G 6854
8.0%
J 6455
 
7.5%
B 6455
 
7.5%
V 5992
 
7.0%
I 5013
 
5.8%
O 1828
 
2.1%
Other values (3) 4428
 
5.2%
ValueCountFrequency (%)
C 4475
18.8%
M 4322
18.2%
H 2336
9.8%
A 2329
9.8%
J 1988
8.4%
B 1988
8.4%
G 1852
7.8%
V 1506
 
6.3%
I 1310
 
5.5%
Á 554
 
2.3%
Other values (3) 1138
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 6854
100.0%
ValueCountFrequency (%)
. 1852
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 606273
93.3%
Common 43258
 
6.7%
ValueCountFrequency (%)
Latin 166026
93.2%
Common 12074
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 80771
 
13.3%
o 56755
 
9.4%
u 44587
 
7.4%
e 36091
 
6.0%
t 34606
 
5.7%
i 31035
 
5.1%
n 30048
 
5.0%
l 29553
 
4.9%
r 29223
 
4.8%
c 22182
 
3.7%
Other values (27) 211422
34.9%
ValueCountFrequency (%)
a 21340
 
12.9%
o 15518
 
9.3%
u 12281
 
7.4%
e 10382
 
6.3%
t 9393
 
5.7%
i 8734
 
5.3%
l 8204
 
4.9%
n 8094
 
4.9%
r 8039
 
4.8%
c 5733
 
3.5%
Other values (27) 58308
35.1%
Common
ValueCountFrequency (%)
36404
84.2%
. 6854
 
15.8%
ValueCountFrequency (%)
10222
84.7%
. 1852
 
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 628890
96.8%
None 20641
 
3.2%
ValueCountFrequency (%)
ASCII 172183
96.7%
None 5917
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 80771
 
12.8%
o 56755
 
9.0%
u 44587
 
7.1%
36404
 
5.8%
e 36091
 
5.7%
t 34606
 
5.5%
i 31035
 
4.9%
n 30048
 
4.8%
l 29553
 
4.7%
r 29223
 
4.6%
Other values (25) 219817
35.0%
ValueCountFrequency (%)
a 21340
 
12.4%
o 15518
 
9.0%
u 12281
 
7.1%
e 10382
 
6.0%
10222
 
5.9%
t 9393
 
5.5%
i 8734
 
5.1%
l 8204
 
4.8%
n 8094
 
4.7%
r 8039
 
4.7%
Other values (25) 59976
34.8%
None
ValueCountFrequency (%)
á 8823
42.7%
é 8162
39.5%
ó 1828
 
8.9%
Á 1828
 
8.9%
ValueCountFrequency (%)
á 2628
44.4%
é 2181
36.9%
Á 554
 
9.4%
ó 554
 
9.4%
 MasculinoFemenino
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB

Procedencia_acta
Unsupported

 MasculinoFemenino
Missing194295808
Missing (%)26.3%28.2%
Memory size1.1 MiB321.9 KiB

Diagnostico_transcrito
['Text', 'Text']

 MasculinoFemenino
Distinct28881326
Distinct (%)3.9%6.4%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:38.572444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length4335
Median length33
Mean length3.52042963.6069608
Min length11

Characters and Unicode

 MasculinoFemenino
Total characters25960074307
Distinct characters7461
Distinct categories99 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique21531028 ?
Unique (%)2.9%5.0%

Sample

 MasculinoFemenino
1st rowS-DS-D
2nd rowS-DS-D
3rd rowS-DS-D
4th rowS-DS-D
5th rowS-DS-D
ValueCountFrequency (%)
s-d 42225
56.3%
tm 5778
 
7.7%
tce 4812
 
6.4%
bn 1387
 
1.8%
tct 920
 
1.2%
cvg 870
 
1.2%
hpafpc 725
 
1.0%
bn+ch 640
 
0.9%
aova 621
 
0.8%
dispensa 603
 
0.8%
Other values (2550) 16428
 
21.9%
ValueCountFrequency (%)
s-d 11287
53.2%
tm 1747
 
8.2%
tce 1196
 
5.6%
bn 517
 
2.4%
cvg 436
 
2.1%
tct 262
 
1.2%
quemaduras 256
 
1.2%
dispensa 239
 
1.1%
hc 199
 
0.9%
aova 183
 
0.9%
Other values (1227) 4914
23.1%
2025-02-11T20:01:38.946203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 43523
16.8%
D 42991
16.6%
- 42235
16.3%
T 20770
 
8.0%
C 14071
 
5.4%
A 9863
 
3.8%
P 9560
 
3.7%
M 7338
 
2.8%
E 7098
 
2.7%
H 5871
 
2.3%
Other values (64) 56280
21.7%
ValueCountFrequency (%)
S 11839
15.9%
D 11612
15.6%
- 11294
15.2%
T 5588
 
7.5%
C 3691
 
5.0%
M 2489
 
3.3%
A 2292
 
3.1%
N 2166
 
2.9%
E 2111
 
2.8%
P 1592
 
2.1%
Other values (51) 19633
26.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 184616
71.1%
Dash Punctuation 42235
 
16.3%
Lowercase Letter 26433
 
10.2%
Math Symbol 4677
 
1.8%
Space Separator 1268
 
0.5%
Other Punctuation 316
 
0.1%
Decimal Number 20
 
< 0.1%
Open Punctuation 18
 
< 0.1%
Close Punctuation 17
 
< 0.1%
ValueCountFrequency (%)
Uppercase Letter 49801
67.0%
Dash Punctuation 11294
 
15.2%
Lowercase Letter 11009
 
14.8%
Math Symbol 1415
 
1.9%
Space Separator 635
 
0.9%
Other Punctuation 128
 
0.2%
Open Punctuation 10
 
< 0.1%
Close Punctuation 8
 
< 0.1%
Decimal Number 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 43523
23.6%
D 42991
23.3%
T 20770
11.3%
C 14071
 
7.6%
A 9863
 
5.3%
P 9560
 
5.2%
M 7338
 
4.0%
E 7098
 
3.8%
H 5871
 
3.2%
N 5785
 
3.1%
Other values (16) 17746
9.6%
ValueCountFrequency (%)
S 11839
23.8%
D 11612
23.3%
T 5588
11.2%
C 3691
 
7.4%
M 2489
 
5.0%
A 2292
 
4.6%
N 2166
 
4.3%
E 2111
 
4.2%
P 1592
 
3.2%
B 1584
 
3.2%
Other values (12) 4837
9.7%
Dash Punctuation
ValueCountFrequency (%)
- 42235
100.0%
ValueCountFrequency (%)
- 11294
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4676
> 99.9%
= 1
 
< 0.1%
ValueCountFrequency (%)
+ 1415
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 3926
14.9%
e 3337
12.6%
a 2693
10.2%
n 1974
 
7.5%
u 1878
 
7.1%
r 1860
 
7.0%
i 1762
 
6.7%
o 1242
 
4.7%
x 1174
 
4.4%
m 1169
 
4.4%
Other values (15) 5418
20.5%
ValueCountFrequency (%)
e 1356
12.3%
s 1269
11.5%
a 1243
11.3%
n 839
 
7.6%
u 835
 
7.6%
r 813
 
7.4%
i 748
 
6.8%
o 622
 
5.6%
m 591
 
5.4%
p 519
 
4.7%
Other values (15) 2174
19.7%
Space Separator
ValueCountFrequency (%)
1268
100.0%
ValueCountFrequency (%)
635
100.0%
Other Punctuation
ValueCountFrequency (%)
. 264
83.5%
? 15
 
4.7%
/ 14
 
4.4%
" 13
 
4.1%
' 5
 
1.6%
, 3
 
0.9%
: 1
 
0.3%
* 1
 
0.3%
ValueCountFrequency (%)
. 107
83.6%
? 8
 
6.2%
" 6
 
4.7%
/ 5
 
3.9%
' 1
 
0.8%
: 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 11
55.0%
4 3
 
15.0%
9 2
 
10.0%
1 1
 
5.0%
5 1
 
5.0%
6 1
 
5.0%
3 1
 
5.0%
ValueCountFrequency (%)
2 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
55.6%
[ 8
44.4%
ValueCountFrequency (%)
( 5
50.0%
[ 5
50.0%
Close Punctuation
ValueCountFrequency (%)
) 9
52.9%
] 8
47.1%
ValueCountFrequency (%)
] 5
62.5%
) 3
37.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 211049
81.3%
Common 48551
 
18.7%
ValueCountFrequency (%)
Latin 60810
81.8%
Common 13497
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 43523
20.6%
D 42991
20.4%
T 20770
9.8%
C 14071
 
6.7%
A 9863
 
4.7%
P 9560
 
4.5%
M 7338
 
3.5%
E 7098
 
3.4%
H 5871
 
2.8%
N 5785
 
2.7%
Other values (41) 44179
20.9%
ValueCountFrequency (%)
S 11839
19.5%
D 11612
19.1%
T 5588
 
9.2%
C 3691
 
6.1%
M 2489
 
4.1%
A 2292
 
3.8%
N 2166
 
3.6%
E 2111
 
3.5%
P 1592
 
2.6%
B 1584
 
2.6%
Other values (37) 15846
26.1%
Common
ValueCountFrequency (%)
- 42235
87.0%
+ 4676
 
9.6%
1268
 
2.6%
. 264
 
0.5%
? 15
 
< 0.1%
/ 14
 
< 0.1%
" 13
 
< 0.1%
2 11
 
< 0.1%
( 10
 
< 0.1%
) 9
 
< 0.1%
Other values (13) 36
 
0.1%
ValueCountFrequency (%)
- 11294
83.7%
+ 1415
 
10.5%
635
 
4.7%
. 107
 
0.8%
? 8
 
0.1%
2 7
 
0.1%
" 6
 
< 0.1%
/ 5
 
< 0.1%
( 5
 
< 0.1%
[ 5
 
< 0.1%
Other values (4) 10
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259600
100.0%
ValueCountFrequency (%)
ASCII 74307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 43523
16.8%
D 42991
16.6%
- 42235
16.3%
T 20770
 
8.0%
C 14071
 
5.4%
A 9863
 
3.8%
P 9560
 
3.7%
M 7338
 
2.8%
E 7098
 
2.7%
H 5871
 
2.3%
Other values (64) 56280
21.7%
ValueCountFrequency (%)
S 11839
15.9%
D 11612
15.6%
- 11294
15.2%
T 5588
 
7.5%
C 3691
 
5.0%
M 2489
 
3.3%
A 2292
 
3.1%
N 2166
 
2.9%
E 2111
 
2.8%
P 1592
 
2.1%
Other values (51) 19633
26.4%

Diagnostico_estandar
['Text', 'Text']

 MasculinoFemenino
Distinct10599
Distinct (%)0.2%0.5%
Missing62751968
Missing (%)8.5%9.6%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:39.135303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length1515
Median length33
Mean length3.13156263.0783019
Min length11

Characters and Unicode

 MasculinoFemenino
Total characters21127457358
Distinct characters2525
Distinct categories44 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique414 ?
Unique (%)< 0.1%0.1%

Sample

 MasculinoFemenino
1st rowS-DS-D
2nd rowS-DS-D
3rd rowS-DS-D
4th rowS-DS-D
5th rowS-DS-D
ValueCountFrequency (%)
s-d 42235
62.6%
tm 5768
 
8.5%
tce 4761
 
7.1%
bn 1345
 
2.0%
tct 915
 
1.4%
hpaf 880
 
1.3%
cvg 859
 
1.3%
hpafpc 780
 
1.2%
dispensa 652
 
1.0%
hpafpt 629
 
0.9%
Other values (97) 8682
 
12.9%
ValueCountFrequency (%)
s-d 11292
60.6%
tm 1744
 
9.4%
tce 1188
 
6.4%
bn 512
 
2.7%
cvg 432
 
2.3%
quem 268
 
1.4%
dispensa 264
 
1.4%
tct 262
 
1.4%
anen 244
 
1.3%
hc 192
 
1.0%
Other values (89) 2236
 
12.0%
2025-02-11T20:01:39.486789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 44501
21.1%
D 42971
20.3%
- 42235
20.0%
T 17822
8.4%
C 10920
 
5.2%
A 8980
 
4.3%
E 7432
 
3.5%
P 7249
 
3.4%
M 6906
 
3.3%
H 3691
 
1.7%
Other values (15) 18567
8.8%
ValueCountFrequency (%)
S 12214
21.3%
D 11611
20.2%
- 11292
19.7%
T 4712
 
8.2%
C 2911
 
5.1%
E 2444
 
4.3%
M 2313
 
4.0%
A 2119
 
3.7%
N 1494
 
2.6%
P 1250
 
2.2%
Other values (15) 4998
8.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 168995
80.0%
Dash Punctuation 42235
 
20.0%
Space Separator 40
 
< 0.1%
Decimal Number 4
 
< 0.1%
ValueCountFrequency (%)
Uppercase Letter 46064
80.3%
Dash Punctuation 11292
 
19.7%
Space Separator 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 44501
26.3%
D 42971
25.4%
T 17822
10.5%
C 10920
 
6.5%
A 8980
 
5.3%
E 7432
 
4.4%
P 7249
 
4.3%
M 6906
 
4.1%
H 3691
 
2.2%
N 3364
 
2.0%
Other values (12) 15159
 
9.0%
ValueCountFrequency (%)
S 12214
26.5%
D 11611
25.2%
T 4712
 
10.2%
C 2911
 
6.3%
E 2444
 
5.3%
M 2313
 
5.0%
A 2119
 
4.6%
N 1494
 
3.2%
P 1250
 
2.7%
V 664
 
1.4%
Other values (12) 4332
 
9.4%
Dash Punctuation
ValueCountFrequency (%)
- 42235
100.0%
ValueCountFrequency (%)
- 11292
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
2 4
100.0%
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 168995
80.0%
Common 42279
 
20.0%
ValueCountFrequency (%)
Latin 46064
80.3%
Common 11294
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 44501
26.3%
D 42971
25.4%
T 17822
10.5%
C 10920
 
6.5%
A 8980
 
5.3%
E 7432
 
4.4%
P 7249
 
4.3%
M 6906
 
4.1%
H 3691
 
2.2%
N 3364
 
2.0%
Other values (12) 15159
 
9.0%
ValueCountFrequency (%)
S 12214
26.5%
D 11611
25.2%
T 4712
 
10.2%
C 2911
 
6.3%
E 2444
 
5.3%
M 2313
 
5.0%
A 2119
 
4.6%
N 1494
 
3.2%
P 1250
 
2.7%
V 664
 
1.4%
Other values (12) 4332
 
9.4%
Common
ValueCountFrequency (%)
- 42235
99.9%
40
 
0.1%
2 4
 
< 0.1%
ValueCountFrequency (%)
- 11292
> 99.9%
1
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 211274
100.0%
ValueCountFrequency (%)
ASCII 57358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 44501
21.1%
D 42971
20.3%
- 42235
20.0%
T 17822
8.4%
C 10920
 
5.2%
A 8980
 
4.3%
E 7432
 
3.5%
P 7249
 
3.4%
M 6906
 
3.3%
H 3691
 
1.7%
Other values (15) 18567
8.8%
ValueCountFrequency (%)
S 12214
21.3%
D 11611
20.2%
- 11292
19.7%
T 4712
 
8.2%
C 2911
 
5.1%
E 2444
 
4.3%
M 2313
 
4.0%
A 2119
 
3.7%
N 1494
 
2.6%
P 1250
 
2.2%
Other values (15) 4998
8.7%

Diagnostico_extendido
['Text', 'Text']

 MasculinoFemenino
Distinct9488
Distinct (%)0.1%0.5%
Missing62751968
Missing (%)8.5%9.6%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:39.692421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

 MasculinoFemenino
Max length4848
Median length99
Mean length14.39628914.495197
Min length55

Characters and Unicode

 MasculinoFemenino
Total characters971260270089
Distinct characters2525
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique310 ?
Unique (%)< 0.1%0.1%

Sample

 MasculinoFemenino
1st rowsin datossin datos
2nd rowsin datossin datos
3rd rowsin datossin datos
4th rowsin datossin datos
5th rowsin datossin datos
ValueCountFrequency (%)
sin 42235
27.5%
datos 42235
27.5%
traumatismo 14257
 
9.3%
craneo 7323
 
4.8%
multiple 5768
 
3.8%
encefalico 4835
 
3.2%
herida 3326
 
2.2%
torax 2960
 
1.9%
fuego 2739
 
1.8%
arma 2739
 
1.8%
Other values (90) 25012
16.3%
ValueCountFrequency (%)
sin 11292
27.2%
datos 11292
27.2%
traumatismo 3950
 
9.5%
craneo 1806
 
4.3%
multiple 1744
 
4.2%
encefalico 1212
 
2.9%
asfixia 692
 
1.7%
torax 611
 
1.5%
bronconeumonia 512
 
1.2%
por 449
 
1.1%
Other values (86) 8017
19.3%
2025-02-11T20:01:39.968266image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 118772
12.2%
s 109529
11.3%
o 93943
9.7%
i 87210
9.0%
85963
8.9%
t 85627
8.8%
n 71991
7.4%
d 52349
 
5.4%
e 48239
 
5.0%
r 45481
 
4.7%
Other values (15) 172156
17.7%
ValueCountFrequency (%)
a 32555
12.1%
s 30620
11.3%
o 25713
9.5%
i 24560
9.1%
t 23570
8.7%
22944
8.5%
n 20604
7.6%
e 14021
 
5.2%
d 13987
 
5.2%
m 12709
 
4.7%
Other values (15) 48806
18.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 885293
91.1%
Space Separator 85963
 
8.9%
Decimal Number 4
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 247144
91.5%
Space Separator 22944
 
8.5%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 118772
13.4%
s 109529
12.4%
o 93943
10.6%
i 87210
9.9%
t 85627
9.7%
n 71991
8.1%
d 52349
5.9%
e 48239
 
5.4%
r 45481
 
5.1%
m 44647
 
5.0%
Other values (13) 127505
14.4%
ValueCountFrequency (%)
a 32555
13.2%
s 30620
12.4%
o 25713
10.4%
i 24560
9.9%
t 23570
9.5%
n 20604
8.3%
e 14021
 
5.7%
d 13987
 
5.7%
m 12709
 
5.1%
r 12552
 
5.1%
Other values (13) 36253
14.7%
Space Separator
ValueCountFrequency (%)
85963
100.0%
ValueCountFrequency (%)
22944
100.0%
Decimal Number
ValueCountFrequency (%)
2 4
100.0%
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 885293
91.1%
Common 85967
 
8.9%
ValueCountFrequency (%)
Latin 247144
91.5%
Common 22945
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 118772
13.4%
s 109529
12.4%
o 93943
10.6%
i 87210
9.9%
t 85627
9.7%
n 71991
8.1%
d 52349
5.9%
e 48239
 
5.4%
r 45481
 
5.1%
m 44647
 
5.0%
Other values (13) 127505
14.4%
ValueCountFrequency (%)
a 32555
13.2%
s 30620
12.4%
o 25713
10.4%
i 24560
9.9%
t 23570
9.5%
n 20604
8.3%
e 14021
 
5.7%
d 13987
 
5.7%
m 12709
 
5.1%
r 12552
 
5.1%
Other values (13) 36253
14.7%
Common
ValueCountFrequency (%)
85963
> 99.9%
2 4
 
< 0.1%
ValueCountFrequency (%)
22944
> 99.9%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 971260
100.0%
ValueCountFrequency (%)
ASCII 270089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 118772
12.2%
s 109529
11.3%
o 93943
9.7%
i 87210
9.0%
85963
8.9%
t 85627
8.8%
n 71991
7.4%
d 52349
 
5.4%
e 48239
 
5.0%
r 45481
 
4.7%
Other values (15) 172156
17.7%
ValueCountFrequency (%)
a 32555
12.1%
s 30620
11.3%
o 25713
9.5%
i 24560
9.1%
t 23570
8.7%
22944
8.5%
n 20604
7.6%
e 14021
 
5.2%
d 13987
 
5.2%
m 12709
 
4.7%
Other values (15) 48806
18.1%

Sexo
Categorical

 MasculinoFemenino
Distinct11
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
Masculino
73741 
Femenino
20601 

Length

 MasculinoFemenino
Max length98
Median length98
Mean length98
Min length98

Characters and Unicode

 MasculinoFemenino
Total characters663669164808
Distinct characters96
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique00 ?
Unique (%)0.0%0.0%

Sample

 MasculinoFemenino
1st rowMasculinoFemenino
2nd rowMasculinoFemenino
3rd rowMasculinoFemenino
4th rowMasculinoFemenino
5th rowMasculinoFemenino

Common Values

ValueCountFrequency (%)
Masculino 73741
100.0%
ValueCountFrequency (%)
Femenino 20601
100.0%

Length

2025-02-11T20:01:40.036451image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Masculino

2025-02-11T20:01:40.081293image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:40.116189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
masculino 73741
100.0%
ValueCountFrequency (%)
femenino 20601
100.0%

Most occurring characters

ValueCountFrequency (%)
M 73741
11.1%
a 73741
11.1%
s 73741
11.1%
c 73741
11.1%
u 73741
11.1%
l 73741
11.1%
i 73741
11.1%
n 73741
11.1%
o 73741
11.1%
ValueCountFrequency (%)
e 41202
25.0%
n 41202
25.0%
F 20601
12.5%
m 20601
12.5%
i 20601
12.5%
o 20601
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 589928
88.9%
Uppercase Letter 73741
 
11.1%
ValueCountFrequency (%)
Lowercase Letter 144207
87.5%
Uppercase Letter 20601
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 73741
100.0%
ValueCountFrequency (%)
F 20601
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 73741
12.5%
s 73741
12.5%
c 73741
12.5%
u 73741
12.5%
l 73741
12.5%
i 73741
12.5%
n 73741
12.5%
o 73741
12.5%
ValueCountFrequency (%)
e 41202
28.6%
n 41202
28.6%
m 20601
14.3%
i 20601
14.3%
o 20601
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 663669
100.0%
ValueCountFrequency (%)
Latin 164808
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 73741
11.1%
a 73741
11.1%
s 73741
11.1%
c 73741
11.1%
u 73741
11.1%
l 73741
11.1%
i 73741
11.1%
n 73741
11.1%
o 73741
11.1%
ValueCountFrequency (%)
e 41202
25.0%
n 41202
25.0%
F 20601
12.5%
m 20601
12.5%
i 20601
12.5%
o 20601
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 663669
100.0%
ValueCountFrequency (%)
ASCII 164808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 73741
11.1%
a 73741
11.1%
s 73741
11.1%
c 73741
11.1%
u 73741
11.1%
l 73741
11.1%
i 73741
11.1%
n 73741
11.1%
o 73741
11.1%
ValueCountFrequency (%)
e 41202
25.0%
n 41202
25.0%
F 20601
12.5%
m 20601
12.5%
i 20601
12.5%
o 20601
12.5%

Edad_transcrito
Real number (ℝ)

 MasculinoFemenino
Distinct126117
Distinct (%)0.4%1.5%
Missing4453412571
Missing (%)60.4%61.0%
Infinite00
Infinite (%)0.0%0.0%
Mean37.43094138.179377
 MasculinoFemenino
Minimum-78-78
Maximum108116
Zeros10
Zeros (%)< 0.1%0.0%
Negative7983
Negative (%)0.1%0.4%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:40.169296image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

 MasculinoFemenino
Minimum-78-78
5-th percentile63
Q12418
median3535
Q35060
95-th percentile7180
Maximum108116
Range186194
Interquartile range (IQR)2642

Descriptive statistics

 MasculinoFemenino
Standard deviation19.99879327.358536
Coefficient of variation (CV)0.534285080.7165789
Kurtosis1.58364251.0585992
Mean37.43094138.179377
Median Absolute Deviation (MAD)1320
Skewness-0.10760519-0.37917509
Sum1093245.5306580.4
Variance399.95173748.4895
MonotonicityNot monotonicNot monotonic
2025-02-11T20:01:40.252972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 1512
 
2.1%
30 1452
 
2.0%
35 1441
 
2.0%
45 1362
 
1.8%
25 1362
 
1.8%
50 1214
 
1.6%
60 989
 
1.3%
20 928
 
1.3%
55 870
 
1.2%
22 752
 
1.0%
Other values (116) 17325
 
23.5%
(Missing) 44534
60.4%
ValueCountFrequency (%)
70 323
 
1.6%
65 271
 
1.3%
60 263
 
1.3%
30 259
 
1.3%
25 256
 
1.2%
20 229
 
1.1%
50 229
 
1.1%
75 228
 
1.1%
35 224
 
1.1%
45 219
 
1.1%
Other values (107) 5529
26.8%
(Missing) 12571
61.0%
ValueCountFrequency (%)
-78 1
 
< 0.1%
-72 78
 
0.1%
0 1
 
< 0.1%
1 96
 
0.1%
1.5 20
 
< 0.1%
2 271
0.4%
2.2 1
 
< 0.1%
2.5 4
 
< 0.1%
3 274
0.4%
3.2 1
 
< 0.1%
ValueCountFrequency (%)
-78 1
 
< 0.1%
-72 80
0.4%
-48 1
 
< 0.1%
-12 1
 
< 0.1%
1 69
 
0.3%
1.5 11
 
0.1%
2 197
1.0%
2.5 2
 
< 0.1%
3 179
0.9%
3.5 4
 
< 0.1%
ValueCountFrequency (%)
-78 1
 
< 0.1%
-72 80
0.1%
-48 1
 
< 0.1%
-12 1
 
< 0.1%
1 69
 
0.1%
1.5 11
 
< 0.1%
2 197
0.3%
2.5 2
 
< 0.1%
3 179
0.2%
3.5 4
 
< 0.1%
ValueCountFrequency (%)
-78 1
 
< 0.1%
-72 78
 
0.4%
0 1
 
< 0.1%
1 96
 
0.5%
1.5 20
 
0.1%
2 271
1.3%
2.2 1
 
< 0.1%
2.5 4
 
< 0.1%
3 274
1.3%
3.2 1
 
< 0.1%

Tipo_restos
Categorical

 MasculinoFemenino
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
Cadáver
71182 
Miembros
 
1511
Feto
 
662
Recién nacido
 
379
Restos óseos
 
7
Cadáver
19503 
Feto
 
462
Miembros
 
384
Recién nacido
 
251
Restos óseos
 
1

Length

 MasculinoFemenino
Max length1313
Median length77
Mean length7.02487087.0247075
Min length44

Characters and Unicode

 MasculinoFemenino
Total characters518021144716
Distinct characters2121
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique01 ?
Unique (%)0.0%< 0.1%

Sample

 MasculinoFemenino
1st rowCadáverCadáver
2nd rowCadáverCadáver
3rd rowCadáverCadáver
4th rowCadáverCadáver
5th rowCadáverCadáver

Common Values

ValueCountFrequency (%)
Cadáver 71182
96.5%
Miembros 1511
 
2.0%
Feto 662
 
0.9%
Recién nacido 379
 
0.5%
Restos óseos 7
 
< 0.1%
ValueCountFrequency (%)
Cadáver 19503
94.7%
Feto 462
 
2.2%
Miembros 384
 
1.9%
Recién nacido 251
 
1.2%
Restos óseos 1
 
< 0.1%

Length

2025-02-11T20:01:40.316127image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Masculino

2025-02-11T20:01:40.364176image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:40.411802image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cadáver 71182
96.0%
miembros 1511
 
2.0%
feto 662
 
0.9%
recién 379
 
0.5%
nacido 379
 
0.5%
restos 7
 
< 0.1%
óseos 7
 
< 0.1%
ValueCountFrequency (%)
cadáver 19503
93.5%
feto 462
 
2.2%
miembros 384
 
1.8%
recién 251
 
1.2%
nacido 251
 
1.2%
restos 1
 
< 0.1%
óseos 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 73748
14.2%
r 72693
14.0%
a 71561
13.8%
d 71561
13.8%
C 71182
13.7%
á 71182
13.7%
v 71182
13.7%
o 2566
 
0.5%
i 2269
 
0.4%
s 1539
 
0.3%
Other values (11) 8538
 
1.6%
ValueCountFrequency (%)
e 20602
14.2%
r 19887
13.7%
d 19754
13.7%
a 19754
13.7%
C 19503
13.5%
á 19503
13.5%
v 19503
13.5%
o 1099
 
0.8%
i 886
 
0.6%
n 502
 
0.3%
Other values (11) 3723
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 443894
85.7%
Uppercase Letter 73741
 
14.2%
Space Separator 386
 
0.1%
ValueCountFrequency (%)
Lowercase Letter 123863
85.6%
Uppercase Letter 20601
 
14.2%
Space Separator 252
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 73748
16.6%
r 72693
16.4%
a 71561
16.1%
d 71561
16.1%
á 71182
16.0%
v 71182
16.0%
o 2566
 
0.6%
i 2269
 
0.5%
s 1539
 
0.3%
b 1511
 
0.3%
Other values (6) 4082
 
0.9%
ValueCountFrequency (%)
e 20602
16.6%
r 19887
16.1%
d 19754
15.9%
a 19754
15.9%
á 19503
15.7%
v 19503
15.7%
o 1099
 
0.9%
i 886
 
0.7%
n 502
 
0.4%
c 502
 
0.4%
Other values (6) 1871
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
C 71182
96.5%
M 1511
 
2.0%
F 662
 
0.9%
R 386
 
0.5%
ValueCountFrequency (%)
C 19503
94.7%
F 462
 
2.2%
M 384
 
1.9%
R 252
 
1.2%
Space Separator
ValueCountFrequency (%)
386
100.0%
ValueCountFrequency (%)
252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 517635
99.9%
Common 386
 
0.1%
ValueCountFrequency (%)
Latin 144464
99.8%
Common 252
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 73748
14.2%
r 72693
14.0%
a 71561
13.8%
d 71561
13.8%
C 71182
13.8%
á 71182
13.8%
v 71182
13.8%
o 2566
 
0.5%
i 2269
 
0.4%
s 1539
 
0.3%
Other values (10) 8152
 
1.6%
ValueCountFrequency (%)
e 20602
14.3%
r 19887
13.8%
d 19754
13.7%
a 19754
13.7%
C 19503
13.5%
á 19503
13.5%
v 19503
13.5%
o 1099
 
0.8%
i 886
 
0.6%
n 502
 
0.3%
Other values (10) 3471
 
2.4%
Common
ValueCountFrequency (%)
386
100.0%
ValueCountFrequency (%)
252
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 446453
86.2%
None 71568
 
13.8%
ValueCountFrequency (%)
ASCII 124961
86.3%
None 19755
 
13.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 73748
16.5%
r 72693
16.3%
a 71561
16.0%
d 71561
16.0%
C 71182
15.9%
v 71182
15.9%
o 2566
 
0.6%
i 2269
 
0.5%
s 1539
 
0.3%
b 1511
 
0.3%
Other values (8) 6641
 
1.5%
ValueCountFrequency (%)
e 20602
16.5%
r 19887
15.9%
d 19754
15.8%
a 19754
15.8%
C 19503
15.6%
v 19503
15.6%
o 1099
 
0.9%
i 886
 
0.7%
n 502
 
0.4%
c 502
 
0.4%
Other values (8) 2969
 
2.4%
None
ValueCountFrequency (%)
á 71182
99.5%
é 379
 
0.5%
ó 7
 
< 0.1%
ValueCountFrequency (%)
á 19503
98.7%
é 251
 
1.3%
ó 1
 
< 0.1%
 MasculinoFemenino
Distinct1515
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
semefo_df_bo_1981
5906 
semefo_df_bo_1979
5869 
semefo_df_bo_1982
5849 
semefo_df_bo_1980
5847 
semefo_df_bo_1977
5497 
Other values (10)
44773 
semefo_df_bo_1978
1688 
semefo_df_bo_1977
1623 
semefo_df_bo_1975
1614 
semefo_df_bo_1976
1592 
semefo_df_bo_1980
1583 
Other values (10)
12501 

Length

 MasculinoFemenino
Max length1717
Median length1717
Mean length1717
Min length1717

Characters and Unicode

 MasculinoFemenino
Total characters1253597350217
Distinct characters1818
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique00 ?
Unique (%)0.0%0.0%

Sample

 MasculinoFemenino
1st rowsemefo_df_bo_1968semefo_df_bo_1968
2nd rowsemefo_df_bo_1968semefo_df_bo_1968
3rd rowsemefo_df_bo_1968semefo_df_bo_1968
4th rowsemefo_df_bo_1968semefo_df_bo_1968
5th rowsemefo_df_bo_1968semefo_df_bo_1968

Common Values

ValueCountFrequency (%)
semefo_df_bo_1981 5906
 
8.0%
semefo_df_bo_1979 5869
 
8.0%
semefo_df_bo_1982 5849
 
7.9%
semefo_df_bo_1980 5847
 
7.9%
semefo_df_bo_1977 5497
 
7.5%
semefo_df_bo_1978 5418
 
7.3%
semefo_df_bo_1976 5289
 
7.2%
semefo_df_bo_1975 5212
 
7.1%
semefo_df_bo_1973 4737
 
6.4%
semefo_df_bo_1974 4425
 
6.0%
Other values (5) 19692
26.7%
ValueCountFrequency (%)
semefo_df_bo_1978 1688
 
8.2%
semefo_df_bo_1977 1623
 
7.9%
semefo_df_bo_1975 1614
 
7.8%
semefo_df_bo_1976 1592
 
7.7%
semefo_df_bo_1980 1583
 
7.7%
semefo_df_bo_1981 1570
 
7.6%
semefo_df_bo_1979 1565
 
7.6%
semefo_df_bo_1982 1472
 
7.1%
semefo_df_bo_1973 1361
 
6.6%
semefo_df_bo_1974 1283
 
6.2%
Other values (5) 5250
25.5%

Length

2025-02-11T20:01:40.454645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Masculino


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

Femenino


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
semefo_df_bo_1981 5906
 
8.0%
semefo_df_bo_1979 5869
 
8.0%
semefo_df_bo_1982 5849
 
7.9%
semefo_df_bo_1980 5847
 
7.9%
semefo_df_bo_1977 5497
 
7.5%
semefo_df_bo_1978 5418
 
7.3%
semefo_df_bo_1976 5289
 
7.2%
semefo_df_bo_1975 5212
 
7.1%
semefo_df_bo_1973 4737
 
6.4%
semefo_df_bo_1974 4425
 
6.0%
Other values (5) 19692
26.7%
ValueCountFrequency (%)
semefo_df_bo_1978 1688
 
8.2%
semefo_df_bo_1977 1623
 
7.9%
semefo_df_bo_1975 1614
 
7.8%
semefo_df_bo_1976 1592
 
7.7%
semefo_df_bo_1980 1583
 
7.7%
semefo_df_bo_1981 1570
 
7.6%
semefo_df_bo_1979 1565
 
7.6%
semefo_df_bo_1982 1472
 
7.1%
semefo_df_bo_1973 1361
 
6.6%
semefo_df_bo_1974 1283
 
6.2%
Other values (5) 5250
25.5%

Most occurring characters

ValueCountFrequency (%)
_ 221223
17.6%
e 147482
11.8%
f 147482
11.8%
o 147482
11.8%
1 83706
 
6.7%
9 83469
 
6.7%
b 73741
 
5.9%
s 73741
 
5.9%
d 73741
 
5.9%
m 73741
 
5.9%
Other values (8) 127789
10.2%
ValueCountFrequency (%)
_ 61803
17.6%
e 41202
11.8%
f 41202
11.8%
o 41202
11.8%
1 23336
 
6.7%
9 23120
 
6.6%
b 20601
 
5.9%
s 20601
 
5.9%
d 20601
 
5.9%
m 20601
 
5.9%
Other values (8) 35948
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 737410
58.8%
Decimal Number 294964
 
23.5%
Connector Punctuation 221223
 
17.6%
ValueCountFrequency (%)
Lowercase Letter 206010
58.8%
Decimal Number 82404
 
23.5%
Connector Punctuation 61803
 
17.6%

Most frequent character per category

Connector Punctuation
ValueCountFrequency (%)
_ 221223
100.0%
ValueCountFrequency (%)
_ 61803
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 147482
20.0%
f 147482
20.0%
o 147482
20.0%
b 73741
10.0%
s 73741
10.0%
d 73741
10.0%
m 73741
10.0%
ValueCountFrequency (%)
e 41202
20.0%
f 41202
20.0%
o 41202
20.0%
b 20601
10.0%
s 20601
10.0%
d 20601
10.0%
m 20601
10.0%
Decimal Number
ValueCountFrequency (%)
1 83706
28.4%
9 83469
28.3%
7 54292
18.4%
8 26505
 
9.0%
6 12633
 
4.3%
2 10105
 
3.4%
0 9880
 
3.3%
5 5212
 
1.8%
3 4737
 
1.6%
4 4425
 
1.5%
ValueCountFrequency (%)
1 23336
28.3%
9 23120
28.1%
7 15741
19.1%
8 7217
 
8.8%
6 3450
 
4.2%
2 2668
 
3.2%
0 2614
 
3.2%
5 1614
 
2.0%
3 1361
 
1.7%
4 1283
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 737410
58.8%
Common 516187
41.2%
ValueCountFrequency (%)
Latin 206010
58.8%
Common 144207
41.2%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 221223
42.9%
1 83706
 
16.2%
9 83469
 
16.2%
7 54292
 
10.5%
8 26505
 
5.1%
6 12633
 
2.4%
2 10105
 
2.0%
0 9880
 
1.9%
5 5212
 
1.0%
3 4737
 
0.9%
ValueCountFrequency (%)
_ 61803
42.9%
1 23336
 
16.2%
9 23120
 
16.0%
7 15741
 
10.9%
8 7217
 
5.0%
6 3450
 
2.4%
2 2668
 
1.9%
0 2614
 
1.8%
5 1614
 
1.1%
3 1361
 
0.9%
Latin
ValueCountFrequency (%)
e 147482
20.0%
f 147482
20.0%
o 147482
20.0%
b 73741
10.0%
s 73741
10.0%
d 73741
10.0%
m 73741
10.0%
ValueCountFrequency (%)
e 41202
20.0%
f 41202
20.0%
o 41202
20.0%
b 20601
10.0%
s 20601
10.0%
d 20601
10.0%
m 20601
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1253597
100.0%
ValueCountFrequency (%)
ASCII 350217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 221223
17.6%
e 147482
11.8%
f 147482
11.8%
o 147482
11.8%
1 83706
 
6.7%
9 83469
 
6.7%
b 73741
 
5.9%
s 73741
 
5.9%
d 73741
 
5.9%
m 73741
 
5.9%
Other values (8) 127789
10.2%
ValueCountFrequency (%)
_ 61803
17.6%
e 41202
11.8%
f 41202
11.8%
o 41202
11.8%
1 23336
 
6.7%
9 23120
 
6.6%
b 20601
 
5.9%
s 20601
 
5.9%
d 20601
 
5.9%
m 20601
 
5.9%
Other values (8) 35948
10.3%

Pagina_PDF
Real number (ℝ)

 MasculinoFemenino
Distinct259259
Distinct (%)0.4%1.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean109.10252105.40508
 MasculinoFemenino
Minimum22
Maximum260260
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
2025-02-11T20:01:40.514412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

 MasculinoFemenino
Minimum22
5-th percentile1211
Q15354
median105103
Q3158151
95-th percentile225219
Maximum260260
Range258258
Interquartile range (IQR)10597

Descriptive statistics

 MasculinoFemenino
Standard deviation66.12482363.33184
Coefficient of variation (CV)0.60607970.6008424
Kurtosis-0.91926089-0.73195057
Mean109.10252105.40508
Median Absolute Deviation (MAD)5349
Skewness0.262796650.28108275
Sum80453292171450
Variance4372.49224010.922
MonotonicityNot monotonicNot monotonic
2025-02-11T20:01:40.588681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 420
 
0.6%
29 416
 
0.6%
32 412
 
0.6%
123 411
 
0.6%
31 411
 
0.6%
28 404
 
0.5%
19 400
 
0.5%
33 398
 
0.5%
119 398
 
0.5%
81 397
 
0.5%
Other values (249) 69674
94.5%
ValueCountFrequency (%)
144 137
 
0.7%
5 136
 
0.7%
127 135
 
0.7%
9 130
 
0.6%
22 129
 
0.6%
102 129
 
0.6%
152 129
 
0.6%
4 127
 
0.6%
155 127
 
0.6%
139 126
 
0.6%
Other values (249) 19296
93.7%
ValueCountFrequency (%)
2 50
 
0.1%
3 330
0.4%
4 381
0.5%
5 372
0.5%
6 395
0.5%
7 390
0.5%
8 354
0.5%
9 351
0.5%
10 340
0.5%
11 387
0.5%
ValueCountFrequency (%)
2 18
 
0.1%
3 111
0.5%
4 127
0.6%
5 136
0.7%
6 110
0.5%
7 117
0.6%
8 113
0.5%
9 130
0.6%
10 110
0.5%
11 121
0.6%
ValueCountFrequency (%)
2 18
 
< 0.1%
3 111
0.2%
4 127
0.2%
5 136
0.2%
6 110
0.1%
7 117
0.2%
8 113
0.2%
9 130
0.2%
10 110
0.1%
11 121
0.2%
ValueCountFrequency (%)
2 50
 
0.2%
3 330
1.6%
4 381
1.8%
5 372
1.8%
6 395
1.9%
7 390
1.9%
8 354
1.7%
9 351
1.7%
10 340
1.7%
11 387
1.9%

Foja_transcrito
Unsupported

 MasculinoFemenino
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
 MasculinoFemenino
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.1 MiB321.9 KiB
conocido
59774 
desconocido
13967 
conocido
18298 
desconocido
2303 

Length

 MasculinoFemenino
Max length1111
Median length88
Mean length8.56821858.3353721
Min length88

Characters and Unicode

 MasculinoFemenino
Total characters631829171717
Distinct characters77
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 MasculinoFemenino
Unique00 ?
Unique (%)0.0%0.0%

Sample

 MasculinoFemenino
1st rowconocidoconocido
2nd rowconocidoconocido
3rd rowconocidoconocido
4th rowconocidoconocido
5th rowconocidoconocido

Common Values

ValueCountFrequency (%)
conocido 59774
81.1%
desconocido 13967
 
18.9%
ValueCountFrequency (%)
conocido 18298
88.8%
desconocido 2303
 
11.2%

Length

2025-02-11T20:01:40.646878image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Masculino

2025-02-11T20:01:40.691059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:40.730042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
conocido 59774
81.1%
desconocido 13967
 
18.9%
ValueCountFrequency (%)
conocido 18298
88.8%
desconocido 2303
 
11.2%

Most occurring characters

ValueCountFrequency (%)
o 221223
35.0%
c 147482
23.3%
d 87708
 
13.9%
n 73741
 
11.7%
i 73741
 
11.7%
e 13967
 
2.2%
s 13967
 
2.2%
ValueCountFrequency (%)
o 61803
36.0%
c 41202
24.0%
d 22904
 
13.3%
n 20601
 
12.0%
i 20601
 
12.0%
e 2303
 
1.3%
s 2303
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 631829
100.0%
ValueCountFrequency (%)
Lowercase Letter 171717
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 221223
35.0%
c 147482
23.3%
d 87708
 
13.9%
n 73741
 
11.7%
i 73741
 
11.7%
e 13967
 
2.2%
s 13967
 
2.2%
ValueCountFrequency (%)
o 61803
36.0%
c 41202
24.0%
d 22904
 
13.3%
n 20601
 
12.0%
i 20601
 
12.0%
e 2303
 
1.3%
s 2303
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 631829
100.0%
ValueCountFrequency (%)
Latin 171717
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 221223
35.0%
c 147482
23.3%
d 87708
 
13.9%
n 73741
 
11.7%
i 73741
 
11.7%
e 13967
 
2.2%
s 13967
 
2.2%
ValueCountFrequency (%)
o 61803
36.0%
c 41202
24.0%
d 22904
 
13.3%
n 20601
 
12.0%
i 20601
 
12.0%
e 2303
 
1.3%
s 2303
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 631829
100.0%
ValueCountFrequency (%)
ASCII 171717
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 221223
35.0%
c 147482
23.3%
d 87708
 
13.9%
n 73741
 
11.7%
i 73741
 
11.7%
e 13967
 
2.2%
s 13967
 
2.2%
ValueCountFrequency (%)
o 61803
36.0%
c 41202
24.0%
d 22904
 
13.3%
n 20601
 
12.0%
i 20601
 
12.0%
e 2303
 
1.3%
s 2303
 
1.3%

Interactions

Masculino

2025-02-11T20:01:30.489996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:32.768980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Masculino

2025-02-11T20:01:30.349876image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:32.633536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Masculino

2025-02-11T20:01:30.554251image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:32.820718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Masculino

2025-02-11T20:01:30.430371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:32.697183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

Masculino

2025-02-11T20:01:40.765587image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Femenino

2025-02-11T20:01:40.923078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Masculino

Bitacora_ingresosConocido_desconocidoEdad_transcritoPagina_PDFProcedencia_alcaldiaTipo_restos
Bitacora_ingresos1.0000.0240.0240.2220.0740.062
Conocido_desconocido0.0241.0000.0520.3340.1830.242
Edad_transcrito0.0240.0521.0000.0280.0550.527
Pagina_PDF0.2220.3340.0281.0000.0350.286
Procedencia_alcaldia0.0740.1830.0550.0351.0000.052
Tipo_restos0.0620.2420.5270.2860.0521.000

Femenino

Bitacora_ingresosConocido_desconocidoEdad_transcritoPagina_PDFProcedencia_alcaldiaTipo_restos
Bitacora_ingresos1.0000.1140.0290.1330.0730.088
Conocido_desconocido0.1141.000-0.1420.3120.1360.522
Edad_transcrito0.029-0.1421.000-0.0720.0550.584
Pagina_PDF0.1330.312-0.0721.0000.0240.372
Procedencia_alcaldia0.0730.1360.0550.0241.0000.056
Tipo_restos0.0880.5220.5840.3720.0561.000

Missing values

Masculino

2025-02-11T20:01:30.731496image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.

Femenino

2025-02-11T20:01:32.916238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.

Masculino

2025-02-11T20:01:31.028814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Femenino

2025-02-11T20:01:33.126086image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Masculino

2025-02-11T20:01:31.273239image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Femenino

2025-02-11T20:01:33.283754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Masculino

IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoConocido_desconocido
2BO_1968_00003S-Darzate paredes juanarzateparedesjuan1968-01-07 00:00:001968-01-0783S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
3BO_1968_00004S-Dalvarez martinez isaacalvarezmartinezisaac1968-01-07 00:00:001968-01-0786S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
5BO_1968_00006S-Darce macedo justoarcemacedojusto1968-01-09 00:00:001968-01-09115S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
6BO_1968_00007S-Dalvarez vela jesusalvarezvelajesus1968-01-02 00:00:001968-01-0222S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
7BO_1968_00008S-Davila ramirez pabloavilaramirezpablo1968-01-10 00:00:001968-01-10137S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
8BO_1968_00009S-Dalvarado aurelioalvarados-daurelio1968-01-10 00:00:001968-01-10139S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
9BO_1968_00010S-Dalvarez almaguer arturoalvarezalmaguerarturo1968-01-10 00:00:001968-01-10132S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
10BO_1968_00011S-Daceves galindo miguelacevesgalindomiguel1968-01-16 00:00:001968-01-16214S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
12BO_1968_00013S-Daragon godinez albinoaragongodinezalbino1968-01-09 00:00:001968-01-0991S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido
13BO_1968_00014S-Dangeles garcia felipe pedroangelesgarciafelipe pedro1968-01-18 00:00:001968-01-18236S-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoNaNCadáversemefo_df_bo_196821conocido

Femenino

IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoConocido_desconocido
0BO_1968_00001S-Dacosta ortega teresaacostaortegateresa1968-01-03 00:00:001968-01-0337S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
1BO_1968_00002S-Davila de cuestas catalinaavilade cuestascatalina1968-01-05 00:00:001968-01-0558S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
4BO_1968_00005S-Darellano viuda de campos ma.arellanoviuda de camposma.1968-01-07 00:00:001968-01-0788S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
11BO_1968_00012S-Dalcantara viuda de borja ma.alcantaraviuda de borjama.1968-01-18 00:00:001968-01-18229S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
15BO_1968_00016S-Daguirre macias saraaguirremaciassara1968-01-19 00:00:001968-01-19254S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
17BO_1968_00018S-Dalvarez ledezma guadalupealvarezledezmaguadalupe1968-01-21 00:00:001968-01-21273S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
25BO_1968_00026S-Daguleta de perez liliaaguletade perezlilia1968-01-27 00:00:001968-01-27373S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
28BO_1968_00029S-Dalmazan bernal beatrizalmazanbernalbeatriz1968-01-30 00:00:001968-01-30410S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196821conocido
39BO_1968_00040S-Darjona ramon eliaarjonaramonelia1968-02-15 00:00:001968-02-15643S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196831 reversoconocido
41BO_1968_00042S-Daguilar olvera tomasaaguilarolveratomasa1968-02-18 00:00:001968-02-18681S-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoNaNCadáversemefo_df_bo_196831 reversoconocido

Masculino

IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoConocido_desconocido
96819BO_1982_07469S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-02 00:00:001982-12-02663513AMinisterio Público 13 (Col Aragón La Villa)Gustavo A. Madero478313a -- 4783S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96820BO_1982_07470S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-06 00:00:001982-12-06672737AMinisterio Público 37 (Col Polanco)Miguel Hidalgo110637a -- 1106S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96824BO_1982_07474S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNNaNNaN1982-12-15 00:00:001982-12-15689732AMinisterio Público 32NaN212932a -- 2129S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96826BO_1982_07476S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNNaNNaN1982-12-26 00:00:001982-12-26713513AMinisterio Público 13 (Col Aragón La Villa)Gustavo A. Madero518713a -- 5187S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96828BO_1982_07478S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-14 00:00:001982-12-14688537AMinisterio Público 37 (Col Polanco)Miguel Hidalgo116037a -- 1160S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96831BO_1982_07481S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-30 00:00:001982-12-30726032AMinisterio Público 32NaN223932a -- 2239S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96832BO_1982_07482S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-31 00:00:001982-12-31727632AMinisterio Público 32NaN527032a -- 5270S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96834BO_1982_07484S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-10-27 00:00:001982-10-27604032AMinisterio Público 32NaN142332a -- 1423S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96835BO_1982_07485S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-10-27 00:00:001982-10-27604134AMinisterio Público 34 (Col Santo Tomás)Miguel Hidalgo145434a -- 1454S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982250155conocido
96836BO_1982_07486S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-03-11 00:00:001982-03-11145337AMinisterio Público 37 (Col Polanco)Miguel Hidalgo22437a -- 224S-DS-Dsin datosMasculinoNaNMiembrossemefo_df_bo_1982251156conocido

Femenino

IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoConocido_desconocido
96806BO_1982_07456S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-18 00:00:001982-11-18636632AMinisterio Público 32NaN199732a -- 1997S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96808BO_1982_07458S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-09 00:00:001982-11-09617132AMinisterio Público 32NaN195032a -- 1950S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96809BO_1982_07459S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-09 00:00:001982-11-09616832AMinisterio Público 32NaN193632a -- 1936S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96810BO_1982_07460S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-23 00:00:001982-11-2362416AMinisterio Público 6 (Col Centro)Cuauhtémoc15026a -- 1502S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96814BO_1982_07464S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-16 00:00:001982-11-16634133AMinisterio Público 33 (Col Jardín Balbuena)Venustiano Carranza151233a -- 1512S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96821BO_1982_07471S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-06 00:00:001982-12-06674537AMinisterio Público 37 (Col Polanco)Miguel Hidalgo113037a -- 1130S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96822BO_1982_07472S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-09 00:00:001982-12-09675337AMinisterio Público 37 (Col Polanco)Miguel Hidalgo179837a -- 1798S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96825BO_1982_07475S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-06 00:00:001982-12-06677033AMinisterio Público 33 (Col Jardín Balbuena)Venustiano Carranza222533a -- 2225S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982249154 reversoconocido
96829BO_1982_07479S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-12-25 00:00:001982-12-25704132AMinisterio Público 32NaN217232a -- 2172S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982250155conocido
96833BO_1982_07483S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-11-08 00:00:001982-11-08616813AMinisterio Público 13 (Col Aragón La Villa)Gustavo A. Madero193613a -- 1936S-DS-Dsin datosFemeninoNaNMiembrossemefo_df_bo_1982250155conocido

Duplicate rows

Masculino

IDNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_estandarProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFConocido_desconocido# duplicates
Dataset does not contain duplicate rows.

Femenino

IDNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_estandarProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFConocido_desconocido# duplicates
Dataset does not contain duplicate rows.